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共 70 条记录，以下是31-40 订阅

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A Meta-technique for Increasing Density of Local Stereo Methods through Iterative Interpolation and Warping

A Meta-technique for Increasing Density of Local Stereo Meth...

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11th canadian conference on computer and robot vision (crv)

作者： Murarka, Aniket Einecke, Nils Honda Res Inst USA Inc 425 Natl AveSuite 100 Mountain View CA 94043 USA Honda Res Inst Europe GmbH D-63073 Offenbach Germany

ISBN: (纸本)9781479943388

Despite much progress in global methods for computing depth from pairs of stereo images, local block matching methods are still immensely popular largely due to low computational cost and ease of implementation. However, such methods usually fail to produce valid depths in several image regions due to various reasons such as violations of a fronto-parallel assumption and lack of texture. In this paper, we present a simple and fast meta-technique for increasing the percentage of valid depths (depth map density) for local methods while keeping the percentage of pixels with erroneous depths, low. In the method, the original disparity map computed by a local stereo method is iteratively improved through a process of depth interpolation and image warping based on the interpolated depth. Image warping gives a mechanism for testing the validity of the interpolated depths allowing for incorrect depths to be discarded. Our results on the KITTI stereo data set demonstrate that, on average, we can increase density by 7-13% after a single iteration, for a 15-29% increase in computation and only a slight change in the outlier percentage, depending on the cost function used for matching.

关键词： Benchmark testing Cameras Computational efficiency Cost function Interpolation Iterative methods Transforms depth map disparity stereo vision warping

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Worst-Case Local Boundary Precision in Global Measures of Segmentation Reproducibility

Worst-Case Local Boundary Precision in Global Measures of Se...

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10th International conference on computer and robot vision (crv)

作者： Eramian, Mark Univ Saskatchewan Dept Comp Sci Saskatoon SK S7N 0W0 Canada

ISBN: (纸本)9780769549835

the commonly used measures for reproducibility of semiautomatic/interactive image segmentation algorithms provide global estimates of the precision of the location of an object boundary in a group of segmentations. the joint Dice similarity coefficient, joint Tanimoto coefficient, generalized Tanimoto coefficient, coefficient of variation of volume, and intra-class correlation coefficient of volume are interpreted with respect to a new explicit measure of worst-case local object boundary precision. Experiments established 95% confidence intervals on this new measure for ranges of global reproducibility measures allowing global measures to be interpreted in terms of worst-case local precision. Joint Tanimoto coefficient and joint Dice coefficient are shown to be highly unstable over variations in the number of segmentations being compared. All of the existing measures of segmentation reproducibility are found to be flawed in a significant way with the exception of the generalized Tanimoto coefficient.

关键词： segmentation reproducibility local precision stability

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Petri net-based cooperation in multi-agent systems

Petri net-based cooperation in multi-agent systems

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4th canadian conference on computer and robot vision

作者： Kotb, Y. T. Beauchemin, S. S. Barron, J. L. Univ Western Ontario Dept Comp Sci London ON N6A 5B7 Canada

ISBN: (纸本)9780769527864

We present a formal framework for robotic cooperation in which we use an extension to Petri nets, known as work-flow nets, to establish a protocol among mobile agents based on the task coverage they maintain. Our choice is motivated by the fact that Petri nets handle concurrency and that goal reachability can be theoretically established. We describe the means by which cooperation is performed with Petri nets and analyze their structural and behavioral characteristics in order to show the correctness of our framework.

关键词： Multi agent systems

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Non-uniform hierarchical geo-consistency for multi-baseline stereo

Non-uniform hierarchical geo-consistency for multi-baseline ...

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4th canadian conference on computer and robot vision

作者： Drouin, Marc-Antoine Trudeau, Martin Roy, Sebastien Univ Montreal DIRO Montreal PQ H3C 3J7 Canada

ISBN: (纸本)9780769527864

We propose a new and flexible hierarchical multi-baseline stereo algorithm that features a non-uniform spatial decomposition of the disparity map. the visibility computation and refinement of the disparity map are integrated into a single iterative framework that does not add extra constraints to the cost function. this makes it possible to use a standard efficient stereo matcher during each iteration. the level of refinement is increased automatically where it is needed in order to preserve a good localization of boundaries. While two graph-theoretic stereo matchers are used in our experiments, our framework is general enough to be applied to many others. the validity of our framework is demonstrated using real imagery with ground truth.

关键词： Stereo vision

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A cue to shading: elongations near intensity maxima

A cue to shading: elongations near intensity maxima

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5th canadian conference on computer and robot vision

作者： Gipsman, Daria Langer, Michael S. McGill Univ Sch Comp Sci Montreal PQ H3A 2A7 Canada

ISBN: (纸本)9780769531533

the human visual system is often able to recognize shading patterns and to discriminate them from surface reflectance patterns. To understand how this ability is possible, we investigate what makes shading patterns special. We study a statistical property of shading patterns, namely that they tend to be more elongated near intensity maxima. Second-order derivatives of shading and of surface height are compared, and it is shown that intensities typically have an elongated structure relative to surface heights, and this elongation is more extreme near intensity maxima. this elongation property is formalized in terms of a skewness statistic on the aspect ratios of iso-intensity vs. iso-height curves.

关键词： shading natural images texture

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MDS-Based Multi-Axial Dimensionality Reduction Model For Human Action Recognition

MDS-Based Multi-Axial Dimensionality Reduction Model For Hum...

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11th canadian conference on computer and robot vision (crv)

作者： Touati, Redha Mignotte, Max Univ Montreal Fac Arts & Sci DIRO Montreal PQ H3C 3J7 Canada

ISBN: (纸本)9781479943388

In this paper, we present an original and efficient method of human action recognition in a video sequence. the proposed model is based on the generation and fusion of a set of prototypes generated from different view-points of the data cube of the video sequence. More precisely, each prototype is generated by using a multidimensional scaling (MDS) based nonlinear dimensionality reduction technique both along the temporal axis but also along the spatial axis (row and column) of the binary video sequence of 2D silhouettes. this strategy aims at modeling each human action in a low dimensional space, as a trajectory of points or a specific curve, for each viewpoint of the video cube in a complementary way. A simple K-NN classifier is then used to classify the prototype, for a given viewpoint, associated with each action to be recognized and then the fusion of the classification results for each viewpoint allow us to significantly improve the recognition rate performance. the experiments of our approach have been conducted on the publicly available Weizmann data-set and show the sensitivity of the proposed recognition system to each individual viewpoint and the efficiency of our multi-viewpoint based fusion approach compared to the best existing state-ofthe- art human action recognition methods recently proposed in the literature.

关键词： Human action recognition Multi-axial reduction of dimensionality Gesture recognition Multidimensional scaling FastMap Weizmann data-set K-Nearest Neighbor

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Topic Models for Image Localization

Topic Models for Image Localization

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10th International conference on computer and robot vision (crv)

作者： Wang, Zheng Qureshi, Faisal Z. Univ Ontario Inst Technol Fac Sci Oshawa ON L1H 7K4 Canada

ISBN: (纸本)9780769549835

We present a new scheme for partitioning geo-tagged reference image database in an effort to speed up (query) image localization while maintaining acceptable localization accuracy. Our method learns a topic model over the reference database, which in turn is used to divide the reference database into scene groups. Each scene group consists of "visually similar" images as determined by the topic model. Next raw Scale-Invariant Feature Transform (SIFT) features are collected from every image in a scene group a Fast Library for Approximate Nearest Neightbours (FLANN) index is constructed. Given a query image, first its scene group is determined using the topic model and then its SIFT features are matched against the corresponding FLANN index. the query image is localized using the location information from the visually similar images in the reference database. We evaluate our approach on Google Map Street View dataset and demonstrate that our method outperforms a competing technique.

关键词： image localization topic models SIFT FLANN visual words

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Wavelet-based light reconstruction from a single image

Wavelet-based light reconstruction from a single image

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4th canadian conference on computer and robot vision

作者： Upright, Cameron Cobzas, Dana Jagersand, Martin Univ Alberta CS Edmonton AB T6G 2M7 Canada

ISBN: (纸本)9780769527864

In this paper we propose a wavelet-based light representation. this representation is used for recovering illumination and reflectance of a scene with known geometry from a single calibrated image. Previous approaches of light estimation reconstruct either a discrete set of infinite light sources or the projection of light on the spherical harmonics basis. the first approach is more suitable for modeling sharp light effects while the second one works best for diffuse scenes. In contrast, we show that the proposed representation is suitable for both diffuse and specular scenes. We compared our technique with the two previously mentioned approaches and found it superior In addition to illumination estimation our algorithm also estimates a Phong surface reflection. Experiments with synthetic and real scenes demonstrate the effectiveness of our method.

关键词： Image reconstruction

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Automatic registration of color and infrared videos using trajectories obtained from a multiple object tracking algorithm

Automatic registration of color and infrared videos using tr...

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5th canadian conference on computer and robot vision

作者： Morin, Francois Torabi, Atousa Bilodeau, Guillaume-Alexandre Ecole Polytech Dept Genie Informat & Genie Logiciel Montreal PQ H3C 3A7 Canada

ISBN: (纸本)9780769531533

the registration of images from multiple types of sensors (particularly infrared sensors and color sensors) is the first step to achieving multi-sensor fusion. this is the subject of this paper. Registration is performed by using the trajectories of the moving objects obtained by a novel multiple object tracking algorithm. the trajectories are matched using a RANSAC-based algorithm. the registration criteria used in this algorithm is based on the number 4 pixels in intersection after overlapping the two images. Results show registration accuracy close to the ground-truth after about 30 frames. the influence of the tracking method used to obtain the trajectories is also investigated.

关键词： Trajectories

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Robust Scuba Diver Tracking and Recovery in Open Water Using YOLOv7, SORT, and Spiral Search 20

Robust Scuba Diver Tracking and Recovery in Open Water Using...

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20th conference on robots and vision (crv)

作者： Lotfi, Faraz Virji, Khalil Dudek, Gregory McGill Univ Comp Sci Dept Montreal PQ Canada

ISBN: (纸本)9798350341393

Target tracking is a classic problem in computer vision, with numerous applications in robotics. However, tracking targets underwater presents additional complications due to the six degrees of freedom nature of the problem and the challenging visual environment. In this paper, we address the problem of robotic underwater tracking of scuba divers by partitioning it into two parts: vision and control. We propose a new approach that exploits a highly-maneuverable underwater robot to perform experiments in open water, coupling sensing and control for improved performance. To evaluate the temporal stability of different tracking paradigms, we introduce a new metric, frame-to-frame variance, which is better suited to assess the smoothness of detections from the vision side. We implement PID controllers for control and a spiral search algorithm for target recovery in case of a tracking failure. Our approach only uses observations in the image plane, eliminating the need for robot localization or camera calibration. Using a tracking-by-detection paradigm that combines YOLOv7 for target detection, a tuned filtering technique for temporal stability, and a spiral search algorithm for target recovery, we demonstrate promising performance for long-term tracking. We evaluate our proposed paradigm on the VDD-C dataset and deploy it on an underwater robot for several experiments in open water. Our outcomes show consistency with the ones in the initial studies, and the spiral search algorithm demonstrates promising performance for recapturing a target after a tracking failure. Our approach delivers promising performance for robust underwater tracking, achieving successful open-water tracking scenarios in the presence of strong water currents.

关键词： Underwater Tracking Human-robot Interaction Tracking-by-Detection Spiral Search Target Recovery Scuba Diver Tracking YOLOv7 SORT robot Control Open Water

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