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Titlebook: Computer Vision – ACCV 2016 Workshops; ACCV 2016 Internatio Chu-Song Chen,Jiwen Lu,Kai-Kuang Ma Conference proceedings 2017 Springer Intern

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书目名称Computer Vision – ACCV 2016 Workshops
副标题ACCV 2016 Internatio
编辑Chu-Song Chen,Jiwen Lu,Kai-Kuang Ma
视频videohttp://file.papertrans.cn/235/234117/234117.mp4
概述Includes supplementary material:
丛书名称Lecture Notes in Computer Science
图书封面Titlebook: Computer Vision – ACCV 2016 Workshops; ACCV 2016 Internatio Chu-Song Chen,Jiwen Lu,Kai-Kuang Ma Conference proceedings 2017 Springer Intern
描述The three-volume set, consisting of LNCS 10116, 10117, and 10118, contains carefully reviewed and selected papers presented at 17 workshops held in conjunction with the 13th Asian Conference on Computer Vision, ACCV 2016, in Taipei, Taiwan in November 2016. The 134 full papers presented were selected from 223 submissions. LNCS 10116 contains the papers selected 
出版日期Conference proceedings 2017
关键词classification; human-machine interaction; image processing; neural network; reinforcement learning
版次1
doihttps://doi.org/10.1007/978-3-319-54427-4
isbn_softcover978-3-319-54426-7
isbn_ebook978-3-319-54427-4Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer International Publishing AG 2017
The information of publication is updating

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https://doi.org/10.1007/978-3-642-45461-5 a new promising device is available, which will – most probably – be used in many future research. In this paper, we present a systematic comparison of the Kinect v1 and Kinect v2. We investigate the accuracy and precision of the devices for their usage in the context of 3D reconstruction, SLAM or
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https://doi.org/10.1007/978-3-642-45461-5location imprecision of image LSs, it often produces many erroneous reconstructions when reconstructing 3D LSs by triangulating corresponding LSs from two images. We propose to solve this problem by first recovering space planes and then back-projecting image LSs onto the recovered space planes to g
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The Neurochemical Effects of Lead,ble to generate superpixel by using RGB or LaB features. To tackle this scenario, we propose a superpixel generation algorithm solely on depth image. We aim the semantically-incoherent superpixel problem on depth image, caused by identical depth value in the vicinity of the border. Our algorithm is
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Marc S. Schwartz,Kurt W. Fischerroblem. In this paper, a non-parametric method is adopted to obtain the depth of a single image. To this end, RGB-D datasets are exploited as the inference basis. Given a query image, a global scene-level retrieval is performed against the dataset, followed by a superpixel-level matching. The superp
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Marc S. Schwartz,Kurt W. Fischernding the principles from the ED algorithm, a fast and robust edge detector able to produce one pixel-wide chains of pixels for the edges in the image. In this paper the ED algorithm is extended to run simultaneously on both images in a stereo-pair. The disparity information is obtained by matching
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