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Titlebook: Computer Vision - ACCV 2014 Workshops; Singapore, Singapore C.V. Jawahar,Shiguang Shan Conference proceedings 2015 Springer International P

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发表于 2025-3-21 17:48:06 | 显示全部楼层 |阅读模式
书目名称Computer Vision - ACCV 2014 Workshops
副标题Singapore, Singapore
编辑C.V. Jawahar,Shiguang Shan
视频video
概述Includes supplementary material:
丛书名称Lecture Notes in Computer Science
图书封面Titlebook: Computer Vision - ACCV 2014 Workshops; Singapore, Singapore C.V. Jawahar,Shiguang Shan Conference proceedings 2015 Springer International P
描述The three-volume set, consisting of LNCS 9008, 9009, and 9010, contains carefully reviewed and selected papers presented at 15 workshops held in conjunction with the 12th Asian Conference on Computer Vision, ACCV 2014, in Singapore, in November 2014. The 153 full papers presented were selected from numerous submissions. LNCS 9008 contains the papers selected for the Workshop on Human Gait and Action Analysis in the Wild, the Second International Workshop on Big Data in 3D Computer Vision, the Workshop on Deep Learning on Visual Data, the Workshop on Scene Understanding for Autonomous Systems and the Workshop on Robust Local Descriptors for Computer Vision. LNCS 9009 contains the papers selected for the Workshop on Emerging Topics on Image Restoration and Enhancement, the First International Workshop on Robust Reading, the Second Workshop on User-Centred Computer Vision, the International Workshop on Video Segmentation in Computer Vision, the Workshop: My Car Has Eyes: Intelligent Vehicle with Vision Technology, the Third Workshop on E-Heritage and the Workshop on Computer Vision for Affective Computing. LNCS 9010 contains the papers selected for the Workshop on Feature and Similari
出版日期Conference proceedings 2015
关键词Affective computing; Automatic body capture; Face recognition; Fast vehicle detection; Gait recognition
版次1
doihttps://doi.org/10.1007/978-3-319-16628-5
isbn_softcover978-3-319-16627-8
isbn_ebook978-3-319-16628-5Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer International Publishing Switzerland 2015
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https://doi.org/10.1057/9781137517173rs. The recognition effects of our framework are evaluated on three benchmark datasets: KTH, Weizmann, and YouTube. The experimental results demonstrate that the hybrid descriptor, facilitated with VLAD encoding method, outperforms traditional descriptors by a large margin.
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Action Recognition Using Hybrid Feature Descriptor and VLAD Video Encodingrs. The recognition effects of our framework are evaluated on three benchmark datasets: KTH, Weizmann, and YouTube. The experimental results demonstrate that the hybrid descriptor, facilitated with VLAD encoding method, outperforms traditional descriptors by a large margin.
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Hand Detection and Tracking in Videos for Fine-Grained Action Recognitionbjects. We validate our method of detecting and tracking hands on VideoPose2.0 dataset and apply our method of classifying actions to the playing-instrument group of UCF-101 dataset. Experimental results show the effectiveness of our approach.
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Online Learning of Binary Feature Indexing for Real-Time SLAM Relocalizationmate nearest neighbor search than LSH. By distributing the online learning into the simultaneous localization and mapping (SLAM) process, we successfully apply the method to SLAM relocalization. Experiments show that camera poses can be successfully recovered in real time even there are tens of thousands of landmarks in the map.
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Linnaeus and the Four Corners of the WorldWe compare the performance of the proposed motion boundary trajectory approach with other state-of-the-art approaches, e.g., trajectory based approach, on a number of human action benchmark datasets (YouTube, UCF sports, Olympic Sports, HMDB51, Hollywood2 and UCF50), and found that the proposed approach gives improved recognition results.
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