Search

This paper proposes an outlier and artifact removal method for multiview stereo. The proposed method introduces the three filters, which check (i) consistency among depth maps and their visibility, (ii) left-right consistency and (iii) consistency between the depth map and color intensity, respectively. The proposed method removes outliers and artifacts from depth maps generated by PatchMatch Multi-View Stereo. We demonstrate that the proposed method exhibits the efficient performance on 3D reconstruction compared with conventional methods through a set of experiments using public datasets and under practical situations.

INTRODUCTION HIV infection is known to cause a variety of central nervous system complications, such as malignant lymphoma (ML), toxoplasma encephalopathy, cryptococcal encephalopathy, progressive multifocal leukoencephalopathy (PML), brain tuberculosis and HIV encephalopathy. In our hospital, we performed brain biopsy for HIV-positive patients with central nervous system lesions suspected malignant lymphoma, or cases difficult to diagnose with blood, cerebrospinal fluid, and imaging alone. In this study, we retrospectively examined HIV-positive patients who underwent brain biopsy at our hospital, and analyzed diagnosis and treatment of patients with ML. Methods HIV-positive patients who underwent brain biopsy in our hospital from January 2010 to April 2019 were examined in this study. We analyzed background factors, preoperative examination results, pathological diagnosis, treatment and prognosis. RESULTS There were 1,894 HIV-positive patients who were treated at our hospital during the period, of which 16 cases underwent a total of 18 brain biopsies. The final diagnosis was 7 ML (6 PCNSL, 1 brain metastasis), 3 toxoplasma encephalopathy, 1 PML, 1 brain tuberculosis, 1 immune reconstitution syndrome, 1 Penicillium marneffei infection, 1 hematoma and one case that could not be diagnosed. In patients with ML, preoperative sIL-2 receptor was higher and EBV positive cases in cerebrospinal fluid tended to be more common (p=0.051, p=0.086, respectively). Five of the six patients with PCNSL were treated at our hospital, four of which were treated with highly active antiretroviral treatment (HAART) and whole-brain irradiation and one with HAARA alone, resulting four with CR and one with SD. Four patients, except one who had sudden death of unknown cause, were still alive without recurrence (median observation period 44.5 months). CONCLUSION At the moment, it is difficult to diagnose ML without brain biopsy. HIV-positive status has been regarded as a poor prognosis factor in PCNSL patients, but the prognosis seems to have improved with HAART.

1. Inter-breed morphological comparisons were made among 11 breeds of Japanese native chickens (Gifujidori, Hinaidori, Shokoku, Totenko, Tomaru, Satsumadori, Shamo, Koshamo, Koeyoshi, Chabo and Nagoya), White Leghorn, broiler chickens (Chunky) and red junglefowl collected in the Philippines, based on results of direct measurements and analysis by computer vision techniques of the skull. 2. Analysis of direct measurements identified two groups of chicken: a small type that included the Chabo, Koshamo, red junglefowl, Gifujidori and Shokoku and a large type that included the remaining breeds studied. These groupings were made based on size determined both in the first (PC1) and second principal component (PC2). The greatest length of the cranium and condylobasal length greatly contributed to the morphological differences between these two groups. 3. Analysis by computer vision techniques, however, identified three groups: the Bantam group (which includes red junglefowl), Shokoku group and Shamo group. White Leghorn clustered within the Shokoku group while the broiler chicken belonged to the Shamo group. The region around the junction of the neural cranium and the visceral cranium contributed greatly to the morphological differences among breeds, both in the PC1 and PC2.

We have been conducting a project to digitize the Bayon temple, located at the center of Angkor-Thom in the kingdom of Cambodia. This is a huge structure, more than 150 meters long on all sides and up to 45 meters high. Digitizing such a large-scale object in fine detail requires developing new types of sensors for obtaining data of various kinds related to irregular positions such as the very high parts of the structure occluded from the ground. In this article, we present a sensing system with a moving platform, referred to as the Flying Laser Range Sensor (FLRS), for obtaining data related to these high structures from above them. The FLRS, suspended beneath a balloon, can be maneuvered freely in the sky and can measure structures invisible from the ground. The obtained data, however, has some distortion due to the movement of the sensor during the scanning process. In order to remedy this issue, we have developed several new rectification algorithms for the FLRS. One method is an extension of the 3D alignment algorithm to estimate not only rotation and translation but also motion parameters. This algorithm compares range data of overlapping regions from ground-based sensors and our FLRS. Another method accurately estimates the FLRS's position by combining range data and image sequences from a video camera mounted on the FLRS. We evaluate these algorithms using a IS-based method and verify that both methods achieve much higher accuracy than previous methods.

In this paper, we investigate conventional registration implementation, consisting of rotation and translation, to design the most precise registration so as to accurately restore the 3D shape of an object. To achieve the most accurate registration, our registration implementation needs robustness against data noise, or initial pose and position of data. To verify the accuracy of our implemented registration, we compare the registration behavior with the registration behavior of conventional methods, and evaluate the numerical accuracy of transformation parameter obtained by our registration. However, registration by rigid-body transformation is not enough for modeling and shape comparison: registration with deformation is needed. In this paper, we extend our robust registration to simultaneously estimate the shape parameter as well as the rigid-body transformation parameter. This extension method assumes that the deformation is formulated strictly from the deformation mechanism. We additionally introduce the applications of our extension method.

Currently, optical devices, such as microscopes and CCD cameras, are utilized for identification of bullets and tool marks in the field of forensic science. While these optical methods are easily manageable and effective, they are under great influence of illumination condition. In other words, appearances of striations through these optical devices have possibility to be changed by lighting condition. Besides these appearance-based approaches, we can utilize three dimensional (3D) geometric data of tool marks that are free from lighting condition. In this study, we focused on 3D geometric data of landmark impressions on fired bullets for identification. We obtained the 3D surface data of tool marks by a confocal microscope and reconstructed virtual impressions on a PC monitor from the geometric data. Furthermore, the 3D data are exploited to numerical matching of two surface shapes. We also visualized the difference of two shapes. In order to do this, two surface models are aligned automatically. In this process, pairings of correspondent points on both surfaces are determined. Distance analysis between these pairs leads to a shape comparison. Since comparison results are visualized, they are intuitive and easily perceptive.

Most existing Multi-View Stereo (MVS) algorithms employ the image matching method using Normalized Cross-Correlation (NCC) to estimate the depth of an object. The accuracy of the estimated depth depends on the step size of the depth in NCC-based window matching. The step size of the depth must be small for accurate 3D reconstruction, while the small step significantly increases computational cost. To improve the accuracy of depth estimation and reduce the computational cost, this paper proposes an efficient image matching method for MVS. The proposed method is based on Phase-Only Correlation (POC), which is a high-accuracy image matching technique using the phase components in Fourier transforms. The advantages of using POC are (i) the correlation function is obtained only by one window matching and (ii) the accurate sub-pixel displacement between two matching windows can be estimated by fitting the analytical correlation peak model of the POC function. Thus, using POC-based window matching for MVS makes it possible to estimate depth accurately from the correlation function obtained only by one window matching. Through a set of experiments using the public MVS datasets, we demonstrate that the proposed method performs better in terms of accuracy and computational cost than the conventional method.

Conventional registration algorithms are mostly concerned with rigid-body transformation parameters between a pair of 3D range images. Our proposed framework aims to determine, in a unified manner, not only such rigid transformation parameters but also various deformation parameters, assuming that the deformation we handle here is strictly defined by some parameterized formulation derived from the deformation mechanism. While conventional registration algorithms usually calculate six parameters (three translation and three rotation parameters), our proposed algorithm estimates deformation parameters as well. In this paper, we describe how we formulated such an algorithm, implemented it, and evaluated its performance.

Scanning from the air is one of the most efficient methods for obtaining 3D data of large-scale objects. For this purpose, we have been developing a flying laser range finder that is suspended under a balloon. Even though the scanning speed of the finder is quite rapid, it is difficult to eliminate the influence of the swing of a balloon. As a result the scanned data have some distortion due to the intra-scanning movement. In order to compensate this intra-scanning movement, we propose a evolutional registration algorithm which not only aligns multiple range images to determine inter-scanning movement parameters, but also rectifies distortion of range image by determining intra-scanning movement parameters. In this paper, we describe our aerial scanning system especially focusing on the design of the flying laser range finder and deformation registration algorithm. To show the effectiveness of our method, we evaluate its performance using synthesized and real data.

Lighting can be expected not only as an illumination but also as an effective environment that shows mental and physical influences to human. Our aim is quantification of the influences in order to utilize the effect of lighting positively. Our goal is realization of comfortable environment with use of light. In this experiment, we quantitated the relation between lighting environment and working efficiency by using the Kraepelin test. We found that human could keep concentration longer period under the environment with varying light than with constant light.