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Real-time software, particularly that used in embedded systems, has unique resource and verification requirements. While embedded software may not have great need for processor and memory resources, the need to prove that computations are performed correctly and within hard time and space constraints is very great. Improvements in hardware and compiler technology mean that functional programming languages are increasingly practical for embedded situations. We present a functional programming language, Ca, built on catamorphisms instead of general recursion, intended for use in static analysis. Ca is not Turing-complete—every program must terminate—but it still provides an excellent framework for building static analysis techniques. Catamorphisms are a general tool which encompass bounded iteration, and allow to traverse any algebraic data structure. We discuss the computational properties of this language, as well as provide a framework for future work in static analysis. [ABSTRACT FROM AUTHOR]

Metric spaces are a very active research field which offers efficient methods for indexing and searching by similarity in large data sets. In this paper we present a new clustering-based method for similarity search called SSSTree. Its main characteristic is that the centers of each cluster are selected using Sparse Spatial Selection (SSS), a technique initially developed for the selection of pivots. SSS is able to adapt the set of selected points (pivots or cluster centers) to the intrinsic dimensionality of the space. Using SSS, the number of clusters in each node of the tree depends on the complexity of the subspace it represents. The space partition in each node will be made depending on that complexity, improving thus the performance of the search operation. In this paper we present this new method and provide experimental results showing that SSSTree performs better than previously proposed indexes. [ABSTRACT FROM AUTHOR]

Ordered binary decision diagrams (OBDDs) are the most common dynamic data structure or representation type for Boolean functions. Among the many areas of application are verification, model checking, computer aided design, relational algebra, and symbolic graph algorithms. Although many even exponential lower bounds on the OBDD size of Boolean functions are known, there are only few functions where the OBDD size is even asymptotically known exactly. In this paper the exact OBDD sizes of the fundamental functions multiplexer and addition of n-bit numbers are determined. [ABSTRACT FROM AUTHOR]

Distributed games [7] allow expression of various distributed program synthesis problems. In such games, a team of Process players compete against a unique Environment player, each Process playing on its own arena, without explicit communications with its teammates. The standard definition of distributed games allows some degree of asynchrony : the Environment can play only on part of the arenas, therefore concealing to some Process players that the play is going on. While this is convenient for modeling distributed problems (especially those that themselves make use of asynchrony), these games are by no means easy to manipulate, and the existing constructions are much more tedious. In this paper, we provide a uniform reduction of any finite state distributed game, synchronous or asynchronous, to a synchronous one with the same number of players. This reduction is shown to be correct in the sense that it preserves the existence of finite state distributed winning strategies for the team of Processes. It is uniform in the sense that it is designed for arbitrary input distributed game without any prior knowledge about its satisfiability. The size of the resulting synchronous game is also linear in the size of the original asynchronous one and, moreover, there is no blowup of the size of the winning strategies. Additional expected preservation properties (e.g. information flows) are studied. Surprisingly, it seems that no such reduction exists for arbitrary (infinite state) strategies. [ABSTRACT FROM AUTHOR]

In this paper we provide several new results concerning word and matrix semigroup problems using counter automaton models. As a main result, we prove a new version of Post's correspondence problem to be undecidable and show its application to matrix semigroup problems, such as Any Diagonal Matrix Problem and Recurrent Matrix Problem. We also use infinite periodic traces in counter automaton models to show the undecidability of a new variation of the Infinite Post Correspondence Problem and Vector Ambiguity Problem for matrix semigroups. [ABSTRACT FROM AUTHOR]

Given a permutation group G ≤ Sn by a generating set, we explore MWP (the minimum weight problem) and SDP (the subgroup distance problem) for some natural metrics on permutations. These problems are know to be NP-hard. We study both exact and approximation versions of these problems. We summarize our main results: For our upper bound results we focus on the Hamming and the l ∞  permutation metrics. For the l ∞  metric, we give a randomized 2O(n) time algorithm for finding an optimal solution to MWP. Interestingly, this algorithm adapts ideas from the Ajtai-Kumar-Sivakumar algorithm for the shortest vector problem in lattices [AKS01]. For the Hamming metric, we again give a 2O(n) time algorithm for finding an optimal solution to MWP. This algorithm is based on the classical Schrier-Sims algorithm for finding pointwise stabilizer subgroups of permutation groups.It is known that SDP is NP-hard([BCW06]) and it easily follows that SDP is hard to approximate within a factor of logO(1)n unless P = NP. In contrast, we show that SDP for approximation factor more than n/logn is not NP-hard unless there is an unlikely containment of complexity classes.For several permutation metrics, we show that the minimum weight problem is polynomial-time reducible to the subgroup distance problem for solvable permutation groups. [ABSTRACT FROM AUTHOR]

The problem of software integrity is traditionally addressed as the static verification of the code before the execution, often by checking the code signature. However, there are no well-defined solutions to the run-time verification of code integrity when the code is executed remotely, which is refer to as run-time remote entrusting. In this paper we present the research challenges involved in run-time remote entrusting and how we intend to solve this problem. Specifically, we address the problem of ensuring that a given piece of code executes on an remote untrusted machine and that its functionalities have not been tampered with both before execution and during run-time. [ABSTRACT FROM AUTHOR]

The tiling problem is the decision problem to determine if a given finite collection of Wang tiles admits a valid tiling of the plane. In this work we give a new proof of this fact based on tiling simulations of certain piecewise affine transformations. Similar proof is also shown to work in the hyperbolic plane, thus answering an open problem posed by R.M.Robinson 1971 [9]. [ABSTRACT FROM AUTHOR]

We outline an algebraic model for describing complex structures obtained through self-assembly of molecular building blocks and show that, with this model, the assembled structure can be associated to a language and it can be determined up to congruence. [ABSTRACT FROM AUTHOR]

We consider the following reoptimization scenario: Given an instance of an optimization problem together with an optimal solution, we want to find a high-quality solution for a locally modified instance. The naturally arising question is whether the knowledge of an optimal solution to the unaltered instance can help in solving the locally modified instance. In this paper, we survey some partial answers to this questions: Using some variants of the traveling salesman problem and the Steiner tree problem as examples, we show that the answer to this question depends on the considered problem and the type of local modification and can be totally different: For instance, for some reoptimization variant of the metric TSP, we get a 1.4-approximation improving on the best known approximation ratio of 1.5 for the classical metric TSP. For the Steiner tree problem on graphs with bounded cost function, which is APX-hard in its classical formulation, we even obtain a PTAS for the reoptimization variant. On the other hand, for a variant of TSP, where some vertices have to be visited before a prescribed deadline, we are able to show that the reoptimization problem is exactly as hard to approximate as the original problem. [ABSTRACT FROM AUTHOR]

Human-computer interaction is a well-established and rich subject that has an impact not only on those who develop computational systems, but also on the users of such systems, the vendors, maintainers, and many more stakeholders who are normally involved in designing and delivering software and computer-based tools. Interaction in this context is seen broadly - in general, it involves three constituting parts: the user, the technology, and the way they work together. One can then study such phenomena as how the users work with a particular technology, what the users prefer, how the technology addresses given issues, etc. In this contribution I want to look at a specific type of user interaction - with semantically enriched content in general, and with ontologies in particular. [ABSTRACT FROM AUTHOR]

The unique characteristic of web applications is that they are supposed to be used by much bigger and diverse set of users and stakeholders. An example application area is e-Learning or business to business interaction. In eLearning environment, various users with different background use the eLearning system to study a discipline. In business to business interaction, different requirements and parameters of exchanged business requests might be served by different services from third parties. Such applications require certain intelligence and a slightly different approach to design. Adpative web-based applications aim to leave some of their features at the design stage in the form of variables which are dependent on several criteria. The resolution of the variables is called adaptation and can be seen from two perspectives: adaptation by humans to the changed requirements of stakeholders and dynamic system adaptation to the changed parameters of environments, user or context. Adaptation can be seen as an orthogonal concern or viewpoint in a design process. In this paper I will discuss design abstractions which are employed in current design methods for web applications. I will exemplify the use of the abstractions on eLearning web applications as well as on applications for business to business interaction based on web services. [ABSTRACT FROM AUTHOR]

Modern Web, which is frequently called Social Web or Web 2.0, celebrates the power of the user community. Most frequently it is associated with the power of users as contributors or various kinds of contents through Wikis, blogs, and resource sharing sites. However, the community power impacts not only the production of Web content, but also the access to all kinds of Web content. A number of research groups worldwide work on social information access techniques, which help users get to the right information using "community wisdom" distilled from tracked actions of those who worked with this information earlier. The paper provides an overview of this research stream focusing on social search, social navigation, and social visualization techniques. [ABSTRACT FROM AUTHOR]

Quantum walks are quantum counterparts of random walks. In the last 5 years, they have become one of main methods of designing quantum algorithms. Quantum walk based algorithms include element distinctness, spatial search, quantum speedup of Markov chains, evaluation of Boolean formulas and search on "glued trees" graph. In this talk, I will describe the quantum walk method for designing search algorithms and show several of its applications. [ABSTRACT FROM AUTHOR]

This paper describes our work on practical stereo vision for mobile robots using commodity hardware. The approach described in this paper is based on line segments, since those provide a lot of information about the environment, provide more depth information than point features, and are robust to image noise and colour variations. However, stereo matching with line segments is a difficult problem due to poorly localized end points and perspective distortion. Our algorithm uses integral images and Haar features for line segment extraction. Dynamic programming is used in the line segment matching phase. The resulting line segments track accurately from one frame to the next, even in the presence of noise. [ABSTRACT FROM AUTHOR]

This paper presents the fusion of monogenic signal processing and differential geometry to enable monogenic analyzing of local intrinsic 2D features of low level image data. New rotational invariant features such as structure and geometry (angle of intersection) of two superimposed intrinsic 1D signals will be extracted without the need of any steerable filters. These features are important for all kinds of low level image matching tasks in robot vision because they are invariant against local and global illumination changes and result from one unique framework within the monogenic scale-space. [ABSTRACT FROM AUTHOR]

We present a direct method to calculate a 6DoF pose change of a monocular camera for mobile navigation. The calculated pose is estimated up to a constant unknown scale parameter that is kept constant over the entire reconstruction process. This method allows a direct calculation of the metric position and rotation without any necessity to fuse the information in a probabilistic approach over longer frame sequence as it is the case in most currently used VSLAM approaches. The algorithm provides two novel aspects to the field of monocular navigation. It allows a direct pose estimation without any a-priori knowledge about the world directly from any two images and it provides a quality measure for the estimated motion parameters that allows to fuse the resulting information in Kalman Filters. We present the mathematical formulation of the approach together with experimental validation on real scene images. [ABSTRACT FROM AUTHOR]

Accurate robot detection and localisation is fundamental in applications which involve robot navigation. Typical methods for robot detection require a model of a robot. However in most applications the availability of such model can not be warranted. This paper discusses a different approach. A method is presented to localise the robot in a complex and dynamic scene based only on the information that the robot is following a previously specified movement pattern. The advantage of this method lies in the ability to detect differently shaped and differently looking robots as long as they perform the previously defined movement. The method has been successfully tested in an indoor environment. [ABSTRACT FROM AUTHOR]

In this paper, we develop a novel algorithm for navigating a mobile robot using the visual potential. The visual potential is computed from an image sequence and optical flow computed from successive images captured by the camera mounted on the robot. We assume that the direction to the destination is provided at the initial position of the robot. Using the direction to the destination, the robot dynamically selects a local pathway to the destination without collision with obstacles. The proposed algorithm does no require any knowledge or environmental maps of the robot workspace. Furthermore, this algorithm uses only a monocular uncalibrated camera for detecting a feasible region of navigation, since we apply the dominant plane detection to detect the feasible region. We present the experimental results of navigation in synthetic and real environments. Additionally, we present the robustness evaluation of optical flow computation against lighting effects and various kinds of textures. [ABSTRACT FROM AUTHOR]

With 3D vision measuring, camera calibration is necessary for extracting metric information from 2D images. We present a new algorithm for camera calibration that only requires a spatial triangle with known size. In our method, the camera is fixed while the triangle is rotated freely at one of its vertices. By taking a few (at least two) pictures of the rotating object at an identical camera view position and direction, the camera intrinsic matrix can be obtained. It advances other traditional methods in that the extrinsic parameters are separated from the intrinsic ones, which simplifies the problem with more efficiency and accuracy. Experiments also show that our method is robust and results in high resolution. [ABSTRACT FROM AUTHOR]

Vision algorithms for robot control are usually context dependent. A state based vision controller can provide both the computational and temporal context for the algorithm. A hierarchical layering enables one or more sub-objectives to be selected. To mimic human behaviour, it is argued that using fuzzy logic is better able to manage the subjective data obtained from images. Fuzzy reasoning is used to control both the transitions between states, and also to directly control the behaviour of the robot. These principles are illustrated with an autonomous guide robot. Preliminary results indicate that this approach enables complex control and vision systems to be readily constructed in a manner that is both modular and extensible. [ABSTRACT FROM AUTHOR]

We report current work on methods for robust fitting of ellipsoids to the shape of the human head in three-dimensional models built from laser scanner acquisitions. A starting ellipsoid is obtained from Principal Component Analysis from mesh vertices; those regions far from the surface of the ellipsoid are penalized (outlier rejection and/or damping). A first method consists in re-calculating iteratively the ellipsoid by PCA, adjusting scales. Another method projects the outliers into the ellipsoid. A third method uses a morphological-error approach, via the difference of the distance fields of the head and its fitting ellipsoid. The ellipsoid orientation, position and scales are then changed in search for a set of parameters minimizing the morphological error. To speedup calculations, only a few orthogonal planes are sampled and the distance field is obtained directly from the triangular mesh elements. Among the intended applications, the restoration of the skullcap is presented. [ABSTRACT FROM AUTHOR]

This paper presents vision based self-localization of tiny autonomous mobile robots in a known but highly dynamic environment. The problem covers tracking the robot position with an initial estimate to global self-localization. The algorithm enables the robot to find its initial position and to verify its location during every movement. The global position of the robot is estimated using trilateration based techniques whenever distinct landmark features are extracted. Distance measurements are used as they require fewer landmarks compared to methods using angle measurements. However, the minimum required features for global position estimation are not available throughout the entire state space. Therefore, the robot position is tracked once a global position estimate is available. Extended Kalman filter is used to fuse information from multiple heterogeneous sensors. Simulation results show that the new method that combines the global position estimation with tracking results in significant performance gain. [ABSTRACT FROM AUTHOR]

In generic object recognition, the performance of local descriptors varies from class category to another. A descriptor may have a good performance on one category and low performance on another. Combining more than one descriptor in recognition can give a solution to this problem. The choice of descriptor's type and number of descriptors to be used is then important. In this paper, we use two different types of descriptors, the Gradient Location-Orientation Histogram (GLOH) and simple color descriptor, for generic object recognition. Boosting is used as the underlying learning technique. The recognition model achieves a performance that is comparable to or better than that of state-of-the-art approaches. [ABSTRACT FROM AUTHOR]

We introduce the problem of autonomous trail following without waypoints and present a vision- and ladar-based system which keeps to continuous hiking and mountain biking trails of relatively low human difficulty. Using a RANSAC-based analysis of ladar scans, trail-bordering terrain is classified as belonging to one of several major types: flat terrain, which exhibits low height contrast between on- and off-trail regions; thickly-vegetated terrain, which has corridor-like structure; and forested terrain, which has sparse obstacles and generally lower visual contrast. An adaptive color segmentation method for flat trail terrain and a height-based corridor-following method for thick terrain are detailed. Results are given for a number of autonomous runs as well as analysis of logged data, and ongoing work on forested terrain is discussed. [ABSTRACT FROM AUTHOR]

Person tracking is a key requirement for modern service robots. But methods for robot vision have to fulfill several constraints: they have to be robust to errors evoked by noisy sensor data, they have to be able to work under real-world conditions, and they have to be fast and computationally inexpensive. In this paper we present an approach for tracking the position of a person in 3D based on a particle filter. In our framework, each particle represents a hypothesis for the 3D position, velocity and size of the person's head being tracked. Two cameras are used for the evaluation of the particles. The particles are weighted by projecting them onto the camera image and applying a color-based perception model. This model uses skin color cues for face tracking and color histograms for body tracking. In contrast to feature-based approaches, our system even works when the person is temporary or partially occluded. [ABSTRACT FROM AUTHOR]

Quality of 3D modelling in means of accuracy and level of detail is based fundamentally on the parameters of the imaging system. All aspects from camera design over calibration up to processing have to be regarded and to be coordinated. The whole system chain has to be realized and controlled. The German Aerospace Center developed a new generation of line cameras called MFC (multi functional camera), which can be applied for spaceborne, airborne and terrestrial data acquisition. Its core is a CCD line module consisting of the imaging detector and the front end electronics. Any desired number of such modules can be combined to build up a custom specific imaging system. Flexible usage of different CCD sensors, USB2 interface, real time noise reduction and image compression are the main parameters of this camera. The application of an inertial measurement unit allows data acquisition with moving platforms. This paper gives an overview about the system parameters. All steps of data processing are introduced and examples of 3D models will be given. State of the art stereo matching algorithms are of prime importance, therefore the applied semi-global matching is described shortly. The quality of data products will be evaluated. ... [ABSTRACT FROM AUTHOR]

In recent years a lot of versatile robots have been developed to work in environments with human. However they are not sufficiently flexible nor safe in terms of interaction with human. In our approach we focused on hand and eye coordination in order to establish a flexible robot control, in which a robot recognizes its environment from the input camera images and equips a soft contacting strategy by impedance control. To recognize the environment, we adopt a method to reconstruct motion from a sequence of monocular images by using a pair of parallel straight line segments, which enables us to obtain linear equations to solve the problem. On the other hand the impedance control strategy conveys a flexible interaction between robots and humans. The strategy can be considered as a passive force control, when something contacts the end-effector of the robot. In order to avoid a collision, we introduce a virtual impedance control which can generate force prior to the contact. Neural networks (hereafter: NN) learning is used to decide parameters for impedance control, in which NNs can obtain parameters during the motion (aka: online learning). The validity of the proposed method was verified through experiments with a multijoint robot manipulator. [ABSTRACT FROM AUTHOR]

The history of stereo analysis of pairs of images dates back more than one hundred years, but stereo analysis of image stereo sequences is a fairly recent subject. Sequences allow time-propagation of results, but also come with particular characteristics such as being of lower resolution, or with less contrast. This article discusses the application of belief propagation (BP), which is widely used for solving various low-level vision problems, for the stereo analysis of night-vision stereo sequences. For this application it appears that BP often fails on the original frames for objects with blurry borders (trees, clouds...). In this paper, we show that BP leads to more accurate stereo correspondence results if it is applied on edge images, where we have decided for the Sobel edge operator, due to its time efficiency. We present the applied algorithm and illustrate results (without, or with prior edge processing) on seven, geometrically rectified night-vision stereo sequences (provided by Daimler research, Germany). [ABSTRACT FROM AUTHOR]

We will demonstrate the sensor and data fusion concept of the 2007 DARPA Urban Challenge vehicle assembled by Team CarOLO, Technische Universität Braunschweig. The perception system is based on a hybrid fusion concept, combining object and grid based approaches in order to comply with the requirements of an urban environment. A variety of sensor systems and technologies is applied, providing a 360 degree view area around the vehicle. Within the object based subsystem, obstacles (static and dynamic) are tracked using an Extended Kalman Filter capable of tracking arbitrary contour shapes. Additionally, the grid based subsystem extracts drivability information about the vehicle's driveway by combining the readings of laser scanners, a mono and a stereo camera system using a Dempster-Shafer based data fusion approach. ... [ABSTRACT FROM AUTHOR]

This paper presents a vision-based color segmentation algorithm suitable for urban environments that separates an image into areas of drivable and non-drivable terrain. Assuming that a part of the image is known to be drivable terrain, other parts of the image are classified by comparing the Euclidean distance of each pixel's color to the mean colors of the drivable area in real-time. Moving the search area depending on each frame's result ensures temporal consistency and coherence. Furthermore, the algorithm classifies artifacts such as white and yellow lane markings and hard shadows as areas of unknown drivability. The algorithm was thoroughly tested on the autonomous vehicle 'Caroline', which was a finalist in the 2007 DARPA Urban Challenge. [ABSTRACT FROM AUTHOR]

This paper reports on AnnieWAY, an autonomous vehicle that is capable of driving through urban scenarios and that has successfully entered the finals of the DARPA Urban Challenge 2007 competition. After describing the main challenges imposed and the major hardware components, we outline the underlying software structure and focus on selected algorithms. A recent laser scanner plays the prominent role in the perception of the environment. It measures range and reflectivity for each pixel. While the former is used to provide 3D scene geometry, the latter allows robust lane marker detection. Mission and maneuver selection is conducted via a concurrent hierarchical state machine that specifically ascertains behavior in accordance with California traffic rules. We conclude with a report of the results achieved during the competition. [ABSTRACT FROM AUTHOR]

This paper discusses a trajectory based recognition algorithm to expand the common approaches for atypical event detection in multi-object traffic scenes and to obtain area-based types of information (e.g. maps of speed patterns, trajectory curvatures or erratic movements). Different views of the same area by more than one camera sensor are necessary, because of the typical limitations of single camera systems, resulting from occlusions by other cars, trees and traffic signs. Furthermore, distributed cooperative multi-camera system (MCS) enables a significant enlargement of the observation area. The fusion of object data from different cameras is done by a multi-target tracking approach. This approach opens up opportunities to identify and specify traffic objects, their location, speed and other characteristic object information. New and consolidated information of traffic participants is derived from the system. [ABSTRACT FROM AUTHOR]

Automatic road-signs recognition is becoming a part of Driver Assisting Systems which role is to increase safety and driving comfort. In this paper we present architecture and obtained results of the Polish project on the road-signs recognition system. A holistic approach was undertaken, focusing on interaction of different components of the system. [ABSTRACT FROM AUTHOR]

Blind spots usually lead to difficulties for drivers to maneuver their vehicles in complicated environments, such as garages, parking spaces, or narrow alleys. This paper presents a vision system which can assist drivers by providing the panoramic image of vehicle surroundings in a bird's-eye view. In the proposed system, there are six fisheye cameras mounted around a vehicle so that their views cover the whole surrounding area. Parameters of these fisheye cameras were calibrated beforehand so that the captured images can be dewarped into perspective views for integration. Instead of error-prone stereo matching, overlapping regions of adjacent views are stitched together by aligning along a seam with dynamic programming method followed by propagating the deformation field of alignment with Wendland functions. In this way the six fisheye images can be integrated into a single, panoramic, and seamless one from a look-down viewpoint. Our experiments clearly demonstrate the effectiveness of the proposed image-stitching method for providing the bird's eye view vision for vehicle surrounding monitoring. [ABSTRACT FROM AUTHOR]

The watchman route problem (WRP) was first introduced in 1988 and is defined as follows: How to calculate a shortest route completely contained inside a simple polygon such that any point inside this polygon is visible from at least one point on the route? So far the best known result for the WRP is an ${\cal O}(n^3 \log n)$ runtime algorithm (with inherent numerical problems of its implementation). This paper gives an $\kappa(\varepsilon)\times {\cal O}(kn)$ approximate algorithm for WRP by using a rubberband algorithm, where n is the number of vertices of the simple polygon, k the number of essential cuts, ε the chosen accuracy constant for the minimization of the calculated route, and κ(ε) equals the length of the initial route minus the length of the calculated route, divided by ε. [ABSTRACT FROM AUTHOR]

Kruppa equation based camera self-calibration is one of the classical problems in computer vision. Most state-of-the-art approaches directly solve the quadratic constraints derived from Kruppa equations, which are computationally intensive and difficult to obtain initial values. In this paper, we propose a new initialization algorithm by estimating the unknown scalar in the equation, thus the camera parameters can be computed linearly in a closed form and then refined iteratively via global optimization techniques. We prove that the scalar can be uniquely recovered from the infinite homography and propose a practical method to estimate the homography from a physical or virtual plane located at a far distance to the camera. Extensive experiments on synthetic and real images validate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

We propose an accurate method for image matching in scenes including repetitive patterns like buildings, walls, and so on. We construct our matching method with two phases: matching between the elements of repetitive regions; matching between the points in the remained regions. We first detect the elements of repetitive patterns in each image and find matches between the elements in the regions without using any descriptors depended on a view-point. We then find matches between the points in the remained regions of the two images using the informations of the detected matches. The advantage of our method is to use an efficient matching information in the repetitive patterns. We show the effectiveness of our method by real image examples. [ABSTRACT FROM AUTHOR]

We present a highly efficient method for estimating the structure and motion from image sequences taken by uncalibrated cameras. The basic principle is to do projective reconstruction first followed by Euclidean upgrading. However, the projective reconstruction step dominates the total computational time, because we need to solve eigenproblems of matrices whose size depends on the number of frames or feature points. In this paper, we present a new algorithm that yields the same solution using only matrices of constant size irrespective of the number of frames or points. We demonstrate the superior performance of our algorithm, using synthetic and real video images. [ABSTRACT FROM AUTHOR]

To be effective in the human world robots must respond to human emotional states. This paper focuses on the recognition of the six universal human facial expressions. In the last decade there has been successful research on facial expression recognition (FER) in controlled conditions suitable for human-computer interaction [1,2,3,4,5,6,7,8]. However the human-robot scenario presents additional challenges including a lack of control over lighting conditions and over the relative poses and separation of the robot and human, the inherent mobility of robots, and stricter real time computational requirements dictated by the need for robots to respond in a timely fashion. Our approach imposes lower computational requirements by specifically adapting model-based techniques to the FER scenario. It contains adaptive skin color extraction, localization of the entire face and facial components, and specifically learned objective functions for fitting a deformable face model. Experimental evaluation reports a recognition rate of 70% on the Cohn-Kanade facial expression database, and 67% in a robot scenario, which compare well to other FER systems. [ABSTRACT FROM AUTHOR]

The objective of this research is to apply markerless Augmented Reality (AR) techniques to aid in the visualisation of robotic helicopter related tasks. Conventional robotic AR applications work well with markers in prepared environments but are infeasible in outdoor settings. In this paper, we present preliminary results from a real time markerless AR system for tracking natural features in an agricultural scene. By constructing a virtual marker under a known initial configuration of the robotic helicopter, camera and the ground plane, the camera pose can be continuously tracked using the natural features from the image sequence to perform augmentation of virtual objects. The experiments are simulated on a mock-up model of an agricultural farm and the results show that the current AR system is capable of tracking the camera pose accurately for translational motions and roll rotations. Future work includes reducing jitter in the virtual marker vertices to improve camera pose estimation accuracy for pitch and yaw rotations, and implementing feature recovery algorithms. [ABSTRACT FROM AUTHOR]

Finding correspondences between sensor measurements obtained at different places is a fundamental task for an autonomous mobile robot. Most matching methods search correspondences between salient features extracted from such measurements. However, finding explicit matches between features is a challenging and expensive task. In this paper we build a local map using a stereo head aided by sonars and propose a method for aligning local maps without searching explicit correspondences between primitives. From objects found by the stereo head, an object probability density distribution is built. Then, the Gauss-Newton algorithm is used to match correspondences, so that, no explicit correspondences are needed. [ABSTRACT FROM AUTHOR]

We consider the epipolar geometry between two omnidirectional images acquired from a single viewpoint catadioptric vision sensor with parabolic mirror. This work in particular deals with the estimation of the respective epipoles. We use conformal geometric algebra to show the existence of a 3× 3 essential matrix, which describes the underlying epipolar geometry. The essential matrix is preferable to the 4× 4 fundamental matrix, which comprises the fixed intrinsic parameters, as it can be estimated from less data. We use the essential matrix to obtain a prior for a stochastic epipole computation being a key aspect of our work. The computation uses the well-tried amalgamation of a least-squares adjustment (LSA) technique, called the Gauss-Helmert method, with conformal geometric algebra. The imaging geometry enables us to assign distinct uncertainties to the image points which justifies the considerable advantage of our LSA method over standard estimation methods. Next to the stochastically optimal position of the epipoles, the method computes the rigid body motion between the two camera positions. In addition, our text demonstrates the effortlessness and elegance with which such problems integrate into the framework of geometric algebra. [ABSTRACT FROM AUTHOR]

This work deals with modeling and tracking of mechanical systems which are given as kinematic chains with restricted degrees of freedom. Such systems may involve many joints, but due to additional restrictions or mechanical properties the joints depend on each other. So-called closed-chain or parallel manipulators are examples for kinematic chains with additional constraints. Though the degrees of freedom are limited, the complexity of the dynamic equations increases rapidly when studied analytically. In this work, we suggest to avoid this kind of analytic integration of interconnection constraints and instead to model them numerically via soft constraints. [ABSTRACT FROM AUTHOR]

Efficient stereo matching algorithms search for corresponding points along the epipolar lines defined by the camera properties and configuration. In real cameras, lens distortions and misaligned cameras lead to sloping curved epipolar lines on the raw images. To minimize latencies in a system designed to produce 3D environment maps in real time, positions on the epipolar lines must be computed rapidly and efficiently. We describe the rectification components of a real-time high resolution stereo system in which two high resolution cameras are connected via FireWire links to an FPGA which removes lens distortion and misalignment errors with minimal latency. Look up tables and interpolations are used to provide a balance between high speed and accuracy. After analysing the loss in accuracy from this approach, we show that, for lenses with significant distortions, tables which contain an entry for every 16th pixel provide accurate interpolated intensities. For better (lower distortion) lenses, the lookup tables can be even smaller. The latency is several scan lines and is determined by the lens distortions and camera misalignments themselves. [ABSTRACT FROM AUTHOR]

Stereo vision is a key technology for understanding natural scenes. Most research concentrates on single image pairs. However, in robotic and intelligent vehicles applications image sequences have to be analyzed. The paper shows that an appropriate evaluation in time gives much better results than classical frame-by-frame reconstructions. We start with the state-of-the art in real-time stereo analysis and describes novel techniques to increase the sub-pixel accuracy. Secondly, we show that static scenes seen from a moving observer can be reconstructed with significantly higher precision, if the stereo correspondences are integrated over time. Finally, an optimal fusion of stereo and optical flow, called 6D-Vision, is described that directly estimates position and motion of tracked features, even if the observer is moving. This eases the detection and tracking of moving obstacles significantly. [ABSTRACT FROM AUTHOR]

Intelligent vehicle systems need to distinguish which objects are moving and which are static. A static concrete wall lying in the path of a vehicle should be treated differently than a truck moving in front of the vehicle. This paper proposes a new algorithm that addresses this problem, by providing dense dynamic depth information, while coping with real-time constraints. The algorithm models disparity and disparity rate pixel-wise for an entire image. This model is integrated over time and tracked by means of many pixel-wise Kalman filters. This provides better depth estimation results over time, and also provides speed information at each pixel without using optical flow. This simple approach leads to good experimental results for real stereo sequences, by showing an improvement over previous methods. [ABSTRACT FROM AUTHOR]

This paper introduces a new algorithm for computing multi-resolution optical flow, and compares this new hierarchical method with the traditional combination of the Lucas-Kanade method with a pyramid transform. The paper shows that the new method promises convergent optical flow computation. Aiming at accurate and stable computation of optical flow, the new method propagates results of computations from low resolution images to those of higher resolution. The resolution of images increases this way for the sequence of images used in those calculations. The given input sequence of images defines the maximum of possible resolution. [ABSTRACT FROM AUTHOR]

In this paper, we present a specific use of the Particle-based Belief Propagation (PBP) algorithm as an approximation scheme for the joint distribution over many random variables with very large or continuous domains. After formulating the problem to be solved as a probabilistic graphical model, we show that by running loopy Belief Propagation on the whole graph, in combination with an MCMC method such as Metropolis-Hastings sampling at each node, we can approximately estimate the posterior distribution of each random variable over the state space. We describe in details the application of PBP algorithm to the problem of sparse Structure from Motion and the dense Stereo Vision with unknown camera constraints. Experimental results from both cases are demonstrated. An experiment with a synthetic structure from motion arrangement shows that its accuracy is comparable with the state-of-the-art while allowing estimates of state uncertainty in the form of an approximate posterior density function. [ABSTRACT FROM AUTHOR]

The analysis of emergency response actions usually concentrates on failures as a means to improve future procedures and emergency plans. In this paper we adopt a resilience approach that focuses on the analysis of successful actions. We use group storytelling to recall the actions performed by emergency teams during an incident. A method aimed at recognizing resilient actions is proposed and its application is illustrated in a real case. [ABSTRACT FROM AUTHOR]