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Silk is one of the national cultural heritage with various motifs and patterns. This research aims to detect and classify the image of the silk cloth based on motive. This research uses Augemented Reality technology with Markerless Marker Tracking method. To display a 3D object, the proposed method uses a special pattern as a marker to recognize the fabric type. As a research sample, the authors used 10 types of bugis silk motifs. From the test results found that markers can detect fabric motifs in bright rooms and undetectable markers in dim rooms. The best distance in detecting markers is 10 cm – 50 cm. Meanwhile at a distance of 110 cm, the marker cannot be detected.

Background Fiducial markers are frequently used before treatment for image‐guided patient setup in radiation therapy (RT), but can also be used during treatment for image‐guided intrafraction motion detection. This report describes our implementation of automatic marker detection with periodic kV imaging (TrueBeam v2.5) to monitor and correct intrafraction motion during prostate RT. Methods We evaluated the reproducibility and accuracy of software fiducial detection using a phantom with 3 implanted fiducial markers. Clinical implementation for patients with intraprostatic fiducials receiving volumetric modulated arc therapy (VMAT) utilized periodic on‐board kV imaging with 10 s intervals during treatment delivery. For each image, the software automatically identified fiducial locations and determined whether their distance relative to planned locations were within a 3 mm tolerance. Motion was corrected if either ≥2 fiducials in a single image or ≥1 fiducial in sequential images were out of tolerance. Results Phantom studies demonstrated poorer performance of linear fiducials compared to collapsible fiducials, and wide variability to accurately detect fiducials across eight software settings. For any given setting, results were relatively reproducible and precise to ~0.5 mm. Across 17 patients treated with a median of 20 fractions, the software recommended a shift in 44% of fractions, and a shift was actually implemented after visual confirmation of movement greater than the 3 mm threshold in 20% of fractions. Adjustment of our approach led to improved accuracy for the latter (n = 7) patient subset. On average, table repositioning added 3.0 ± 0.3 min to patient time on table. Periodic kV imaging increased skin dose by an estimated 1 cGy per treatment arc. Conclusions Periodic kV imaging with automatic detection of motion during VMAT prostate treatments is commercially available, and can be successfully implemented to mitigate effects of intrafraction motion with careful attention to software settings.

Purpose: To quantitatively evaluate and compare the image recognition performance of multiple fiducial markers available in real-time tumor-tracking radiation therapy (RTRT). Methods: Clinically available markers including sphere shape, coil shape, cylinder shape, line shape, and ball shape (folded line shape) were evaluated in liver and lung models of RTRT. Maximum thickness of the polymethyl metacrylate (PMMA) phantom that could automatically recognize the marker was determined by template-pattern matching. Image registration accuracy of the fiducial marker was determined using liver RTRT model. Lung RTRT was mimicked with an anthropomorphic chest phantom and a one-dimensional motion stage in order to simulate marker motion in heterogeneous fluoroscopic images. The success or failure of marker tracking and image registration accuracy for the lung model were evaluated in the same manner as that for the liver model. Results: All fiducial markers except for line shape and coil shape of thinner diameter were recognized by the PMMA phantom, which is assumed to have the typical thickness of an abdomen, with two-dimensional image registration accuracy of < 2 pixels. Three-dimensional calculation error with the use of real-time stereoscopic fluoroscopy in RTRT was thought to be within 1 mm. In the evaluation using the lung model, the fiducial markers were recognized stably with sufficient accuracy for clinical application. The same was true for the evaluation using the liver model. Conclusions: The image recognition performance of fiducial markers was quantified and compared. The results presented here may be useful for the selection of fiducial markers.

Spine surgery is nowadays performed for a great number of spine pathologies; it is estimated that 4.83 million surgeries are carried out globally each year. This prevalence led to an evolution of spine surgery into an extremely specialized field, so that traditional open interventions to the spine were integrated and often replaced by minimally invasive approaches. Despite the several benefits associated to robotic minimally invasive surgeries (RMIS), loss of depth perception, reduced field of view and consequent difficulty in intraoperative identification of relevant anatomical structures are still unsolved issues. For these reasons, Augmented Reality (AR) was introduced to support the surgeon in surgical applications. However, even though the irruption of AR has promised breakthrough changes in surgery, its adoption was slower than expected as there are still usability hurdles. The objective of this work is to introduce a client software with marker-based optical tracking capabilities, included into a client-server architecture that uses protocols to enable real-time streaming over the network, providing desktop rendering power to the head mounted display (HMD). Results relative to the tracking are promising (Specificity = 0.98 ± 0.03; Precision = 0.94 ± 0.04; Dice = 0.80 ± 0.07) as well as real-time communication, which was successfully set.

Virtual Reality (VR) technology has become cheaper over time and makes it possible to own. However, interaction techniques in VR need to be natural as possible to be accepted by users. Compared to other computing devices (e.g., mobile and desktop), there is very few human-computer interactions (HCI) paradigms in VR and a lot of HCI issues and problems are yet to be solved. In this paper, we present a VR Welding Kit, a virtual reality welding training simulation developed for mobile smartphones using multiple marker images as an interaction method. The experimental results have revealed with comparison benchmark with high-end VR device, Oculus Quest to see the efficiency of multiple marker interaction with a current VR technology device. System Usability Scales (SUS) also used to see the acceptance between users with this new interaction. This is the first evaluation of combination VR with marker-based tracking method interaction. Simulator Sickness Questionnaire (SSQ) are used to check the cybersickness between participants toward multiple marker interaction. The results on performance shows that mobile VR have a large gap completion compared with Oculus Quest. The SUS score is 73.33, above 68 which is great. SSQ surveys result shows that participant almost feels none in simulation sickness.

Innovative lighting and dynamic sound systems as well as adaptive object mapping solutions constitute a rapidly developing branch of lighting technology and multimedia technology. In order to make it possible to adjust the content to specific objects in the scene, it is necessary to correctly identify them and place them in the accepted frame of reference. Dynamic identification and tracking of objects can be carried out based on two particular types of input data: data from markers installed on objects and data from digital recording systems, founding the operation on infrared (IR), visible light (RGB) and the most advanced RGB-D (RGB and depth) analysis. Most systems used today are those that use various types of markers. This paper presents the advantages and disadvantages of such solutions as well as a target system for dynamic identification and mapping of objects and the human body based on the analysis of data from digital RGB-D cameras. Analyses of identification times, implementation of perspective transformations and 3D-to-2D transformations have been carried out in relation to a planar and cuboidal moving surface. Time analyses have been performed in relation to the resolution of registered and processed images.

A multi-medium motion capture system based on markers&rsquo, visual detection is developed and experimentally demonstrated for monitoring underwater intelligent agents such as fish biology and bionic robot-fish. Considering the refraction effect between air and water, a three-dimensional (3D) reconstruction model is established, which can be utilized to reconstruct the 3D coordinate of markers underwater from 2D data. Furthermore, the process of markers matching is undertaken through the multi-lens fusion perception prediction combined K-Means clustering algorithm. Subsequently, in order to track the marker of being occluded, according to the kinematics information of fish, an improved Kalman filtering algorithm is proposed. Finally, the feasibility and effectiveness of proposed system are verified through experimental results. The main models and methods in this paper can provide a reference and inspiration for measurement of underwater intelligent agents.

Optical marker tracking is used in research environments to understand the dynamics of moving objects of interest. Due to the complexity of the systems and the wide field of applications, there is no simple method to assess system accuracy. In this approach, a driver clubhead functioned as a rigid body and was tracked during the delivery phase of the golf swing. Marker tracking uncertainty was assessed by measures of inter-marker distance errors. The effect of swing speed on marker tracking uncertainty was tested in the range 0 m/s (static) to 50 m/s. Results demonstrated that the rigid body position in the capture volume has a large effect on marker tracking uncertainty. Positive correlations were found between marker tracking uncertainty and swing speed. Marker size and number of cameras used for marker reconstruction were optimised to provide mean marker tracking uncertainties around the tee position of below 0.13 mm.

Augmented reality (AR) can enable physicians to “see” inside of patients by projecting cross-sectional imaging directly onto the patient during procedures. In order to maintain workflow, imaging must be quickly and accurately registered to the patient. We describe a method for automatically registering a CT image set projected from an augmented reality headset to a set of points in the real world as a first step towards real-time registration of medical images to patients. Sterile, radiopaque fiducial markers with unique optical identifiers were placed on a patient prior to acquiring a CT scan of the abdomen. For testing purposes, the same fiducial markers were then placed on a tabletop as a representation of the patient. Our algorithm then automatically located the fiducial markers in the CT image set, optically identified the fiducial markers on the tabletop, registered the markers in the CT image set with the optically detected markers and finally projected the registered CT image set onto the real-world markers using the augmented reality headset.The registration time for aligning the image set using 3 markers was 0.9 ± 0.2 seconds with an accuracy of 5 ± 2 mm. These findings demonstrate the feasibility of fast and accurate registration using unique radiopaque markers for aligning patient imaging onto patients for procedural planning and guidance.

Lower limb injuries, especially those related to the knee joint, are some of the most common and severe injuries among sport practitioners. Consequently, a growing interest in the identification of subjects with high risk of injury has emerged during last years. One of the most commonly used injury risk factor is the measurement of joint angles during the execution of dynamic movements. To that end, techniques such as human motion capture and video analysis have been widely used. However, traditional procedures to measure joint angles present certain limitations, which makes this practice not practical in common clinical settings. This work presents SPIRA, a novel 2D video analysis system directed to support practitioners during the evaluation of joint angles in functional tests. The system employs an infrared camera to track retro-reflective markers attached to the patient’s body joints and provide a real-time measurement of the joint angles in a cost-and-time-effective way. The information gathered by the sensor is processed and managed through a computer application that guides the expert during the execution of the tests and expedites the analysis of the results. In order to show the potential of the SPIRA system, a case study has been conducted, performing the analysis with the both the proposed system and a gold-standard in 2D offline video analysis. The results (ICC( $$\rho$$ ) = 0.996) reveal a good agreement between both tools and prove the reliability of SPIRA.

Patient tracking is an essential part in a surgical augmented reality system for correct hologram to patient registration. Augmented reality can support a surgeon with visual assistance to navigate more precisely during neurosurgical interventions. In this work, a system for patient tracking based on infrared markers is proposed. These markers are widely used in medical applications and meet the special medical requirements such as sterilizability. A tracking accuracy of 0.76 mm is achieved when using the near field reflectivity and depth sensor of the HoloLens. On the HoloLens a performance of 55–60 fps is reached, which grants a sufficiently stable placement of the holograms in the operating room.

This work assesses the accuracy of mono and stereo vision-based marker tracking on the Microsoft HoloLens as a representative of current generation AR devices. This is motivated by the need to employ object tracking in industrial AR applications. We integrate mono and stereo vision-based marker tracking with the HoloLens. A calibration procedure is developed that allows users to assess the accuracy of the calibration alignments by walking around the virtual calibration target. This can be generally applied when calibrating additional tracking systems with ready-made AR systems. Finally, the accuracy that can be achieved with the developed system is evaluated (comparing the influence of different parameters).

We present preliminary results from an ongoing project at the University of Southampton that aims to develop protocols for motion capture with music conducting. These protocols will facilitate the study of conducting gestures, provide a high-quality open-access data set using professional conductors and provide a platform for developing machine learning for conductor following systems. In this paper we explore the potential use of force-plate data to track conductors' beats as a non-intrusive method for conductor following. Three conductors were captured directing the same piece of music and we analysed a section of the piece where the conductors are working with a click-track to ensure the intended beats share the same timing and there is an inherent ground truth. We then examined the data from force plate and high-end optical marker tracking, against observer beat tapping and click audio to determine whether force plate data could serve as a useful analogue in conductor following. The results suggest that with simple analysis of the data, beats can be extracted with comparable timing accuracy to optical marker tracking.

Evaluation of robotic experiments requires physical robots as well as position sensing systems. Accurate systems detecting sufficiently all necessary degrees of freedom, like the famous Vicon system, are commonly too expensive. Therefore, we target an economical multi-camera based solution by following these three requirements: Using multiple cameras to track even large laboratory areas, applying fiducial marker trackers for pose identification, and fuse tracking hypothesis resulting from multiple cameras via extended Kalman filter (i.e. ROS's robot\_localization). While the registration of a multi-camera system for collaborative tracking remains a challenging issue, the contribution of this paper is as follows: We introduce the framework of Cognitive Interaction Tracking (CITrack). Then, common fiducial marker tracking systems (ARToolKit, AprilTag, ArUco) are compared with respect to their maintainability. Lastly, a graph-based camera registration approach in SE(3), using the fiducial marker tracking in a multi-camera setup, is presented and evaluated.

Marker-based measurement has been used to assess human body positioning, but human marker tracking has yet to make the transition from the laboratory to personal computing devices, such as smartphones. A novel smartphone-based approach could use a fiducial marker system. Fiducial markers are applicable to augmented reality, robotics, and other applications where a camera-object pose is required and tracked. However, few fiducial systems can be implemented on a mobile phone because of the processing requirements for identifying and tracking the tags in realtime. In augmented reality, virtual information is shared with the real world to further enhance a person’s view of the environment; therefore, this illusion is directly associated with good registration of both virtual and real worlds. Measurement applications also require accurate and fast registration so that real objects are in alignment with virtual objects in real-time. Our research reviewed and evaluated various fiducial marker systems by developing an Android mobile application for real-time biomechanical measurement. A test was designed for two nominated fiducial systems to compare their speed and robustness on the mobile phone. AprilTag2 was selected as the best fiducial marker option for this application.

Target motion–induced uncertainty in particle therapy is more complicated than that in X-ray therapy, requiring more accurate motion management. Therefore, a hybrid motion-tracking system that can track internal tumor motion and as well as an external surrogate of tumor motion was developed. Recently, many correlation tests between internal and external markers in X-ray therapy have been developed; however, the accuracy of such internal/external marker tracking systems, especially in particle therapy, has not yet been sufficiently tested. In this article, the process of installing an in-house hybrid internal/external motion-tracking system is described and the accuracy level of tracking system was acquired. Our results demonstrated that the developed in-house external/internal combined tracking system has submillimeter accuracy, and can be clinically used as a particle therapy system as well as a simulation system for moving tumor treatment.

SummaryX-ray reconstruction of moving morphology (XROMM) uses biplanar videoradiography and computed tomography (CT) scanning to capture three-dimensional (3D) bone motion. In XROMM, morphologically accurate 3D bone models derived from CT are animated with motion from videoradiography, yielding a highly accurate and precise reconstruction of skeletal kinematics. We employ this motion analysis technique to characterize metacarpophalangeal joint (MCPJ) motion in the absence and presence of protective legwear in a healthy pony. Our in vivo marker tracking precision was 0.09 mm for walk and trot, and 0.10 mm during jump down exercises. We report MCPJ maximum extension (walk: –27.70 ± 2.78° [standard deviation]; trot: –33.84 ± 4.94°), abduction/adduction (walk: 0.04 ± 0.24°; trot: –0.23 ± 0.35°) and external/internal rotations (walk: 0.30 ± 0.32°; trot: –0.49 ± 1.05°) indicating that the MCPJ in this pony is a stable hinge joint with negligible extra-sagittal rotations. No substantial change in MCPJ maximum extension angles or vertical ground reaction forces (GRFv) were observed upon application of legwear during jump down exercise. Neoprene boot application yielded –65.20 ± 2.06° extension (GRFv = 11.97 ± 0.67 N/kg) and fleece polo wrap application yielded –64.23 ± 1.68° extension (GRFv = 11.36 ± 1.66 N/kg), when compared to naked control (-66.11 ± 0.96°; GRFv = 12.02 ± 0.53 N/kg). Collectively, this proof of concept study illustrates the benefits and practical limitations of using XROMM to document equine MCPJ kinematics in the presence and absence of legwear.Supplementary Material to this article is available online at https://doi.org/10.3415/VCOT-16-06-0095.

Scale model is a necessary building design in architecture as a way for architects to represent the results of the design as a physical model. The making of scale model requires components that costs some money. With the development of Augmented Reality (AR) technology, designer could bring the model design without having to make a scale model through marker tracking on a brochure. However, with the development of the technology itself, the researcher applies an AR method that can put an object in real environment by detecting flat surfaces. The method is Markerless AR. With this method, the use of marker tracking which requires a marker to remain on the frame of the camera is no longer needed. The technique in the new method will use plane detection that can detect flat surfaces by specifying points on the textures of the frame which is captured by the camera. The necessary stage is to define point cloud that will be used to mark the textures and the plane as a place to put the model in the form of virtual object. Object placed above the plane will remain stable despite having the camera moves around it, the plane will not move around because it is a result of virtual projections. The result of using plane detection will provide a space for the user to observe the model more clearly, such as on a floor or on a table because the model can be rescaled and rotated. Users also can move freely without being hindered by the marker tracking.

Human motion capture by optical sensors produces snapshots of the motion of a cloud of points that need to be labeled in order to carry out ensuing motion analysis for medical or other purposes. We generate the labeling of instantaneous captures of the cloud of points, discarding temporal correlations, in the presence of occlusions. Our approach proposes an ensemble of weak classifiers defined over geometrical features extracted from small subsets of the cloud of points. We apply an Adaboost strategy to select a minimal ensemble of weak classifiers achieving a target correct labeling detection accuracy. Furthermore, we use these features to generate the labeling of the points in the cloud even in the presence of occlusions.To deal with the occlusions of markers we search for ensembles of partial labeling solvers which can provide partial consistent labelings which cover the unoccluded markers. We test two greedy search approaches and a genetic algorithm in the search for the optimal ensemble of partial solvers We demonstrate the approach on a real dataset obtained from the measurement of gait motion of persons, with available ground truth labeling. Results are encouraging, achieving high accuracy label generation at a reduced computational cost. (C) 2019 The Author(s). Published by Elsevier B.V. The work in this paper has been partially supported by FEDER funds for the MINECO project TIN2017-85827-P, and projects KK-2018/00071 and KK-2018/00082 of the Elkartek 2018 funding program of the Basque Government. This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 777720.

One of the challenges of mobile eye tracking is mapping gaze data on a reference image of the stimulus. Here we present a marker-tracking system that relies on the scene-video, recorded by eye tracking glasses, to recognize and track markers and map gaze data on the reference image. Due to the simple nature of the markers employed, the current system works with low-quality videos and at long distances from the stimulus, allowing the use of mobile eye tracking in new situations.

The quality of ARToolKit markers plays a vital role in the performance of Augmented Reality applications, but currently there is no algorithm or quantitative measure to guide users for designing high quality markers and their reliable tracking. This paper presents eleven factors that are important for designing and tracking ARToolKit markers. The effect of each factor on the quality (accuracy, detection speed, and inter-marker confusion) of marker tracking system is investigated and the optimal value(s) of these factors are found. Using the optimal values of these factors one can achieve the goal of reliable and robust tracking of fiducial markers.

International audience; Fiducial markers are images or landmarks placed in real environment, typically used for pose estimation and camera tracking. Reliable fiducials are strongly desired for many augmented reality (AR) applications, but currently there is no systematic method to design highly reliable fiducials. In this paper, we present fiducial marker optimizer (FMO), a tool to optimize the design attributes of ARToolKit markers, including black to white (B:W) ratio, edge sharpness, and information complexity, and to reduce inter-marker confusion. For these operations, the FMO provides a user friendly interface at the front-end and specialized image processing algorithms at the back-end. We tested manually designed markers and FMO optimized markers in ARToolKit and found that the latter were more robust. The FMO will be used for designing highly reliable fiducials in easy to use fashion. It will improve the application's performance, where it is used.

This paper presents a three-dimensional (3-D) measurement method of large-scale objects by integrating a 3-D scanner and a stereo tracker. To measure a large-scale object, some high-brightness light-emitting diode (LED) lights are rigidly connected to the 3-D scanner. During measurement, the stereo tracker remains stationary, and the 3-D scanner is moved to measure partial sections of a large object. Meanwhile, the LED lights are tracked by the stereo tracker to compute the poses of the 3-D scanner for aligning partial sections. The performance and effectiveness are evaluated by experiments.

Speeding-up of computational capabilities has greatly augmented the capture accuracy of motion pictures. That technology has been widely applied in the field of entertainment, sports, public welfare, and medical services. Today, motion capture has general versatility for its marker tracking technology. However, it is possible that marker tracking accuracy depends on the measurement. This paper describes assessment of capture accuracy for different configurations of measurements.

The article presents a hybrid monitoring technique for the measurement of the deformation field. The goal is to obtain information about crack propagation in existing structures, for the purpose of monitoring their state of health. The measurement technique is based on the capture and analysis of a digital image set. Special markers were used on the surface of the structures that can be removed without damaging existing structures as the historical masonry. The digital image analysis was done using software specifically designed in Matlab to follow the tracking of the markers and determine the evolution of the deformation state. The method can be used in any type of structure but is particularly suitable when it is necessary not to damage the surface of structures. A series of experiments carried out on masonry walls of the Oliverian Museum (Pesaro, Italy) and Palazzo Silvi (Perugia, Italy) have allowed the validation of the procedure elaborated by comparing the results with those derived from traditional measuring techniques.

The report contains a description of augmented reality technology application in the education and training of mechanical engineers. Software for augmented reality marker tracking for mechanical engineering education is created and described. An approach for design a textbook with 3D models of cutting tools, measuring tools and special equipment, visualised using augmented reality is presented.

This paper describes the design and implementation of a novel augmented reality application, referred as FunPianoAR, that aiming to activate the interests of user and improve the experience of piano learning. The FunPianoAR with a user-friendly interface considers the paired play to further reduce the difficulty of playing the piano for adult novices. For the paired play, one user plays the melody and the other plays the harmony part. The app is developed by using Android Studio 3.0 and artoolkitX 1.0, an open source augmented reality SDK, and installed on the AR smart glasses, Epson Moverio BT300. Due to the textureless features of real piano and registration precision, the application is implemented by using the fiducial marker tracking instead of the markerless recognition. Besides, we divided the piano keyboard into four zones and each zone used a separate marker for tracking to solve the limited field of view (FOV) to some extent. The virtual keys can be accurately superimposed on the piano keys by using multi-marker tracking. An evaluation was also conducted to compare the effects of two types of augmented reality information superimposed, i.e., the instant way without the hints for the next note to be played and the FunPianoAR with the hints for the coming notes to be played. The correctness rate was calculated and the time differences between the notes that two players should play at the same time were collected. The FunPianoAR shows more advantages over the instant way based on the evaluation results.

We propose a novel hybrid inertial sensors-based indoor pedestrian dead reckoning system, aided by computer vision-derived position measurements. In contrast to prior vision-based or vision-aided solutions, where environmental markers were used—either deployed in known positions or extracted directly from it—we use a shoe-fixed marker, which serves as positional reference to an opposite shoe-mounted camera during foot swing, making our system self-contained. Position measurements can be therefore more reliably fed to a complementary unscented Kalman filter, enhancing the accuracy of the estimated travelled path for 78%, compared to using solely zero velocities as pseudo-measurements.

A novel vibration source separation and identification method using the denoising source separation (DSS) technique is proposed for the mixed mechanical vibration signals from engines in ships. Denoising source separation enables us to extract the source signals from the mixed signals without prior knowledge of sources and their mixing mode, and thus the important source information extracted by DSS can be used to monitor or actively control engine noises. Different denoising functions such as energy, skew, kurtosis, and tangential functions in DSS are applied to both simulation studies and experimental data to evaluate their separating performances. The tangential function provides the best outperformance with both numerical study and engineering application. In addition, the effectiveness of the proposed DSS method is validated by correlation analysis and the frequency marker tracking method.

Recent research has enabled in-vivo examination of mucociliary transit in live airways by analysing the movement patterns of micron-sized markers in high resolution synchrotron X-ray images. However, high levels of false positives and false negatives severely impact the performance of many automated tracking algorithms. This paper proposes an improved approach to track valid mucociliary transit markers using a modified gating region and cost matrix. The proposed method offers a more effective way to associate markers with the correct trackers. Improved visualization methods are also introduced to assist the interpretation of the tracking results. The tracking method has achieved a tracking accuracy of 81.7% track purity and 71.3% track effectiveness. Refereed/Peer-reviewed

Marker systems are a widely used optical tracking method that does not support occlusions. Thus, this paper proposes a new marker design to overcome the problem of marker occlusions. It is highly adaptable, because it can be used by any marker tracking system that uses its central area to codify the digital identification. Our proposal takes advantage of an untapped frame to place some textures that will be tracked during marker occlusion. In addition, these textures are customizable, which lets users make their own designs. Two tracking methods are combined to offer a robust tracking, updating the six degrees of freedom of the camera in real time. The first one is a fast technique based on temporal coherence, whereas the second one is a robust technique based on appearance, which is used as a recovery mode. Copyright © 2012 John Wiley & Sons, Ltd.

However, in order to create a stereoscopic 3D image, independently, it is required to spend expensive manufacturing costs and to have special techniques. As 3D display devices have been generalized, there is an increasing need for implementing a stereoscopic 3D image without a burden of expensive costs. This paper proposes some methods to implement stereoscopic 3D images easily by utilizing a marker tracking technology using a single camera. In addition, the study made it possible for the resolution of an image to be adjustable dynamically. This paper will be committed to the promotion of the field of UCC (User Created Contents) using stereoscopic 3D images by attracting the active participation of general users in the field of the implementation of stereoscopic 3D images.

The authors conducted a study aiming at applying Augmented Reality technology in the field of architecture. There are some problems in the method of marker tracking when it is applied in the field of architecture. The authors groped the solutions which don't depend only on the method of marker tracking. The solution for indoor uses a 3-axis orientation sensor and marker tracking. The solution for outdoor uses a 3-axis orientation sensor and RTK-GPS. In this paper, how the system was implemented and evaluated is described in detail.

Accepted: 2009-01-12, 資料番号: SA1000721000

Ocular torsion is a key problem in the understanding of many visual perceptual effects. However, since it is difficult to record, its integration with other sensorimotor signals is still poorly understood. Unfortunately, eyetracker systems are generally not dedicated to the monitoring of eye torsion. In addition, the classical methods used with video-based systems present some limits in the accuracy of torsion calculation. These limits are especially related to the detection of pupil center and the effects of pupil size changes. This article aims at (1) proposing a solution to analyze ocular torsion together with head roll using EyeLink II or similar equipment, (2) reviewing and adapting classical polar cross-correlation methods in order to improve the accuracy of torsion measurement, (3) providing a lower-cost method compared with the existing ones. Video sequences issued from the EyeLink II host computer monitor were recorded by means of a second computer equipped with a video acquisition card and converted into image sequences. Images were analyzed with algorithms of pupil center detection (median-based algorithm), torsion analysis (adapted polar cross-correlation method which takes into account pupil size variations) and marker tracking (head roll analysis). This method was tested on virtual eye images. Results are discussed with respect to other algorithms found in the literature.

Videofluoroscopy (VF) is one of the most commonly used tools to assess oropharyngeal dysphagia as well as to visualize musculoskeletal structures of humans and animals engaged in various behaviors, including feeding. Despite its importance in clinical and scientific use, processing VF data has historically been extremely tedious because it is performed using manual frame-by-frame methods. With recent technological advances, the frame rate for scientific use has been increasing along with the use of high speed data capture systems. In the current study, we used non-human primates as a model animal to study human feeding behaviors to capture tongue movement based on markers implanted into the tongue. Here, we introduce a semi-automatic marker tracking algorithm that yields high tracking accuracy (> 90%) and dramatic speed improvements (faster than real time labeling). Furthermore, we quantify the sources of tracking errors and the tracking performance as a function of marker speeds. Our results indicate that there is more room for methodological improvements both in detection and prediction of marker positions. Moreover, correspondingly faster frame rates will be required to capture faster kinematic behaviors such as those of mice, which are extensively used to study both control and pathological conditions.

Respiration can cause tumor movements in thoracic regions of up to 3 cm. To minimize motion effects several approaches, such as gating and deep inspiration breath hold (DIBH), are still under development. The goal of our study was to develop and evaluate a noninvasive system for gated DIBH (GDIBH) based on external markers. DIBH monitoring was based on an infrared tracking system and an in-house-developed software. The in-house software provided the breathing curve in real time and was used as on-line information for a prototype of a feedback device. Reproducibility and stability of the breath holds were evaluated without and with feedback. Thirty-five patients undergoing stereotactic body radiotherapy (SBRT) performed DIBH maneuvers after each treatment. For 16 patients dynamic imaging sequences on a multislice CT were used to determine the correlation between tumor and external markers. The relative reproducibility of DIBH maneuvers was improved with the feedback device (74.5%{+-}17.1% without versus 93.0%{+-}4.4% with feedback). The correlation between tumor and marker was good (Pearson correlation coefficient 0.83{+-}0.17). The regression slopes showed great intersubject variability but on average the internal margin in a DIBH treatment situation could be theoretically reduced by 3 mm with the feedback device. DIBH monitoring could be realizedmore » in a noninvasive manner through external marker tracking. We conclude that reduction of internal margins can be achieved with a feedback system but should be performed with great care due to the individual behavior of target motion.« less

For solving complex tasks cooperatively in close interaction with robots, they need to understand natural human communication. To achieve this, robots could benefit from a deeper understanding of the processes that humans use for successful communication. Such skills can be studied by investigating human face-to-face interactions in complex tasks. In our work the focus lies on shared-space interactions in a path planning task and thus 3D gaze directions and hand movements are of particular interest. However, the analysis of gaze and gestures is a time-consuming task: Usually, manual annotation of the eye tracker's scene camera video is necessary in a frame-by-frame manner. To tackle this issue, based on the EyeSee3D method, an automatic approach for annotating interactions is presented: A combination of geometric modeling and 3D marker tracking serves to align real world stimuli with virtual proxies. This is done based on the scene camera images of the mobile eye tracker alone. In addition to the EyeSee3D approach, face detection is used to automatically detect fixations on the interlocutor. For the acquisition of the gestures, an optical marker tracking system is integrated and fused in the multimodal representation of the communicative situation.

Objective:Experimental testingof annuloplastyring (AR) effectsrequires a control groupif the AR is implanted conventionally. Our goal was to develop a reversible AR insertion method that allows for beating heart assessment with and without an AR, providing the ability to evaluate the effects of an AR in the same animal (internal control). We tested the feasibility of this technique in an in vivo ovine model using four-dimensional (4-D) radiopaque marker tracking. Methods: Before the operation, a rigid AR (Edwards Geoform W , Edwards Lifesciences, Irvine, CA, USA) was prepared by stitching the middle parts of eight double-armed sutures evenly spaced through the ring fabric using a Spring Eye needle. The resulting loops were ‘locked’ with polypropylene sutures. In addition, two drawstring sutures were attached to the AR. Using cardiopulmonary bypass and cardioplegic arrest,12 adultsheephad 16 radiopaque markers sewnto the mitralannulus. The ARwas implanted by stitchingthe eight suturesequidistantlyina perpendiculardirectionthroughthemitralannulus.Thesheepweretransferredto thecatheterisationlaboratoryand4D marker coordinates were obtained using biplane videofluoroscopy (60 Hz) with the AR inserted (Geo-AR). The locking sutures were then released, the AR was pulled up to the atrial roof using the drawstring sutures and another dataset was acquired (control). Maximum and minimum mitral annularareas (MAAmax, MAAmin) duringthe cardiac cycle were derived from implanted markers. Data are provided from one representative animal. Results: AR insertion and release were uneventful in all animals. Whereas the mitral annulus was dynamic in the control state (MAAmax: 9.0 cm 2 , MAAmin: 7.8 cm 2 ), mitral annular dynamics were abolished in the Geo-AR case (MAAmax: 6.2 cm 2 , MAAmin: 6.0 cm 2 ). Conclusions: This novel releasable AR implantation method is feasible and permits in vivo assessment of AR effects in the same heart. The new technique should facilitate experimental AR testing and promote the development of ARs based on physical criteria. # 2009 European Association for Cardio-Thoracic Surgery. Published by Elsevier B.V. All rights reserved.

In this paper we introduce a new method for 6DoF marker tracking, specially designed for Microsoft SecondLight or any camera-based tabletop interface that is able to see objects through the surface. Our method is based on topological region adjacency for the identification of the markers, which are fitted into a squared shape for properly track the marker pose in the real world. We also describe the constraints imposed by the system which will determine the size and ID range of the new markers, and we finally evaluate the system.

The in-depth analysis of heart movements under varying conditions is an important problem of cardiac surgery. To reveal the movement of relevant muscular parts, biplanar X-ray recordings of implanted radio-opaque markers are acquired. As manually locating these markers in the images is a very time-consuming task, our goal is to automate this process. Taking into account the difficulties in the recorded data such as missing detections or 2D occlusions, we propose a two-stage graph-based approach for both 3D tracklet and 3D track generation. In the first stage of our approach, we construct a directed acyclic graph of 3D observations to obtain tracklets via shortest path optimization. Afterwards, full tracks are extracted from a tracklet graph in a similar manner. This results in a globally optimal linking of detections and tracklets, while providing a flexible framework which can easily be adapted to various tracking scenarios based on the edge cost functions. We validate our approach on an X-ray sequence of a beating sheep heart based on manually labeled ground-truth marker positions. The results show that the performance of our method is comparable to human experts, while standard 3D tracking approaches such as particle filters are outperformed.

Background 3D motion analysis represents a method of collecting objective, accurate and repeatable gait data, however the high cost of equipment inhibits its widespread use in routine clinical practice. Objective To determine the marker tracking accuracy of a new low-cost optical 3D motion analysis system. Design Comparative between-system study. Setting Clinical motion analysis laboratories. Methods A rigid cluster of four reflective markers was used to compare a low-cost Optitrack 3D motion analysis system against two more expensive systems (Vicon 612 and Vicon MX). Accuracy was measured by comparing the mean vector magnitudes (between each combination of markers) for each system, and reliability was measured through the coefficients of variation (CV). Gaps in the marker trajectories, which are considered undesirable, were also counted. Results In terms of accuracy, the largest disagreement between mean vector magnitudes for Optitrack and Vicon MX was 2.2%. The largest disagreement between Vicon 612 and Vicon MX was 2.1%. Regarding reliability, the mean CV was lowest in Vicon MX (0.3%) and similar in the Vicon 612 (2.5%) and Optitrack (2.3%) systems. The number of trajectory gaps for the Vicon MX, Vicon 612 and Optitrack systems were; zero, six and 11 respectively. Conclusions The Optitrack system provides a low-cost 3D motion analysis system that can offer marker tracking accuracy and reliability which is comparable with an older and still widely used system (Vicon 612). Further development work is required before Optitrack can be used for full 3D gait analysis by physiotherapists and other health professionals.

We developed a novel marker tracking method with shape-free designable markers, which can be visually meaningful to users. The method can work fast enough to provide a real-time camerabased interaction even on low performance CPUs such as one used in mobile Internet devices. Features such as visually communicative design and inexpensive computational cost are very desirable for users with mobile devices in the mobile/pervasive interaction environment. The method utilizes the topological region adjacency to detect the marker candidates and then apply a simple method similar to geometric-hashing to determine the detected maker by voting to the hash tables. By such a combination of two different approaches, our method can distinguish those markers with the same topological structure and is also capable of 6-DoF post estimation whereas most of the existing topology-based systems can not distinguish markers with the same topological.

Markers are widely used for camera-based interaction. Yet, most of the marker tracking methods have considerable limitations in shapes and designs; they are not usually visually meaningful to the users. Such an issue on visually communicative designs can be very important to provide visual cues in a mobile/pervasive environment where a user must first notice a marker and understand its meaning before initiating interaction, unlike in an immersive environment with a head-mounted-display that keeps displaying information on the detected markers.

The Face Cube is a work of interactive art which is targeted to children. To implement this art work, we use a camera-projector system. Instead of rear projection and edge detection method, we choose front projection approach and histogram-based detection method for interaction. This paper describes how to design the Face Cube and marker design for robust interaction, efficient way to remove projection lights from the front projection system for marker recognition, histogram-based marker detection, marker information management.