8,780 research outputs found
Accurate Optical Flow via Direct Cost Volume Processing
We present an optical flow estimation approach that operates on the full
four-dimensional cost volume. This direct approach shares the structural
benefits of leading stereo matching pipelines, which are known to yield high
accuracy. To this day, such approaches have been considered impractical due to
the size of the cost volume. We show that the full four-dimensional cost volume
can be constructed in a fraction of a second due to its regularity. We then
exploit this regularity further by adapting semi-global matching to the
four-dimensional setting. This yields a pipeline that achieves significantly
higher accuracy than state-of-the-art optical flow methods while being faster
than most. Our approach outperforms all published general-purpose optical flow
methods on both Sintel and KITTI 2015 benchmarks.Comment: Published at the Conference on Computer Vision and Pattern
Recognition (CVPR 2017
A New Approach for Stereo Matching Algorithm with Dynamic Programming
Stereo matching algorithms are one of heavily researched topic in binocular stereo vision. Massive 3D information can be obtained by finding correct correspondence of different points between images captured from different views. Development of stereo matching algorithm is done for obtaining disparity maps i.e. depth information. When disparities computed for scan lines then dense reconstruction becomes time consuming for vision navigation systems. So for pair of stereo images proposed method extracts features points those are at contours in images and then a dynamic program is used to find the corresponding points from each image and calculates disparities. Also to reduce the noise which may lead to incorrect results in stereo correspondence, a new stereo matching algorithm based on the dynamic programming is proposed. Generally dynamic programming finds the global minimum for independent scan lines in polynomial time. While efficient, its performance is far from desired one because vertical consistency between scan lines is not enforced. This method review the use of dynamic programming for stereo correspondence by applying it to a contour instead to individual scan lines. Proposed methodology will obtain the global minimum for contour array in linear time using Longest Common Subsequent (LCS) dynamic programming method with no disparity space image (DSI).
DOI: 10.17762/ijritcc2321-8169.15025
Research on robust salient object extraction in image
制度:新 ; 文部省報告番号:甲2641号 ; 学位の種類:博士(工学) ; 授与年月日:2008/3/15 ; 早大学位記番号:新480
Optical techniques for 3D surface reconstruction in computer-assisted laparoscopic surgery
One of the main challenges for computer-assisted surgery (CAS) is to determine the intra-opera- tive morphology and motion of soft-tissues. This information is prerequisite to the registration of multi-modal patient-specific data for enhancing the surgeon’s navigation capabilites by observ- ing beyond exposed tissue surfaces and for providing intelligent control of robotic-assisted in- struments. In minimally invasive surgery (MIS), optical techniques are an increasingly attractive approach for in vivo 3D reconstruction of the soft-tissue surface geometry. This paper reviews the state-of-the-art methods for optical intra-operative 3D reconstruction in laparoscopic surgery and discusses the technical challenges and future perspectives towards clinical translation. With the recent paradigm shift of surgical practice towards MIS and new developments in 3D opti- cal imaging, this is a timely discussion about technologies that could facilitate complex CAS procedures in dynamic and deformable anatomical regions
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