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Titlebook: Computer Vision - ECCV 2014 Workshops; Zurich, Switzerland, Lourdes Agapito,Michael M. Bronstein,Carsten Rothe Conference proceedings 2015

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Gait-Based Person Identification Using Motion Interchange Patternspturing local changes in motion directions. Our scheme does not rely on silhouettes commonly used in gait recognition, and benefits from the capability of MIP encoding to model real world videos. We empirically demonstrate the effectiveness of this modeling of human motion on several challenging gait recognition datasets.
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Weight-Optimal Local Binary Patternsve shown that the WoLBP gains significant performance improvement over traditional LBP, and such WoLBP learning procedure can be directly ported to many other LBP variants to further improve their performances.
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Conference proceedings 2015onjunction with the 13th European Conference on Computer Vision, ECCV 2014, held in Zurich, Switzerland, in September 2014..The 203 workshop papers were carefully reviewed and selected for inclusion in the proceedings. They where presented at workshops with the following themes: where computer visio
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0302-9743 dings of the Workshops that took place in conjunction with the 13th European Conference on Computer Vision, ECCV 2014, held in Zurich, Switzerland, in September 2014..The 203 workshop papers were carefully reviewed and selected for inclusion in the proceedings. They where presented at workshops with
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https://doi.org/10.1007/978-1-4612-6007-3ental results show that Ffirst exceeds the best reported results in texture classification on three difficult texture datasets KTH-TIPS2a, KTH-TIPS2b and ALOT, achieving 88 %, 76 % and 96 % accuracy respectively. The recognition rates are above 99 % on standard texture datasets KTH-TIPS, Brodatz32, UIUCTex, UMD, CUReT.
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https://doi.org/10.1007/978-1-4612-6007-3pturing local changes in motion directions. Our scheme does not rely on silhouettes commonly used in gait recognition, and benefits from the capability of MIP encoding to model real world videos. We empirically demonstrate the effectiveness of this modeling of human motion on several challenging gait recognition datasets.
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Product Families for Mass Customizationve shown that the WoLBP gains significant performance improvement over traditional LBP, and such WoLBP learning procedure can be directly ported to many other LBP variants to further improve their performances.
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