Title: | Pose-specific pedestrian classificatiion using multiple features in par-infrared images |
Authors: | Kim, Dong-Seok Park, Ki-Yeong |
Citation: | WSCG 2015: full papers proceedings: 23rd International Conference in Central Europeon Computer Graphics, Visualization and Computer Visionin co-operation with EUROGRAPHICS Association, p. 161-164. |
Issue Date: | 2015 |
Publisher: | Václav Skala - UNION Agency |
Document type: | konferenční příspěvek conferenceObject |
URI: | wscg.zcu.cz/WSCG2015/CSRN-2501.pdf http://hdl.handle.net/11025/29513 |
ISBN: | 978-80-86943-65-7 (print) 978-80-86943-61-9 (CD-ROM) |
ISSN: | 2464–4617 (print) 2464–4625 (CD-ROM) |
Keywords: | více funkcí;zadání šablony;infračervené snímky;pedestrian classification |
Keywords in different language: | multi-features;pose templates;far-infrared images;klasifikace chodců |
Abstract: | We present a multiple feature-based, pose-specific pedestrian classification approach to improve classification performance for fair-infrared (FIR) images. Using pose-specific classifiers and multiple features has proved to be beneficial in visible-spectrum-based classification systems; therefore, we adapt both to an FIR-based classification system. For pose-specific classifiers, we separate poses into sets of front/back and right/left poses and estimate the pose using template matching. For feature extraction, we use histograms of local intensity differences (HLID) and local binary patterns (LBP). Experiments showed that the proposed approaches improve the classification performance of a baseline HLID/linSVM approach. |
Rights: | © Václav Skala - UNION Agency |
Appears in Collections: | WSCG 2015: Full Papers Proceedings |
Please use this identifier to cite or link to this item:
http://hdl.handle.net/11025/29513
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