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Object Localization with Global and Local Context Kernels
Published on Dec 01, 20095400 Views
Recent research has shown that the use of contextual cues significantly improves performance in sliding window type localization systems. In this work, we propose a method that incorporates both globa
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Chapter list
Object Localization with Global and Local Context Kernels00:00
Outline00:02
Sliding window localization00:28
Identify all Objects in an Image00:33
Sliding Window Parametrization00:48
Compatibility Function01:08
Joint kernel maps for localization02:01
Joint Kernel Maps02:02
Joint Kernel between Images and Boxes: Restriction Kerne03:08
Restriction Kernel: Examples03:52
Problem (1)04:25
Problem (2)04:34
Contextual cues04:40
Global and Local Context Kernels (1)04:44
Global and Local Context Kernels (2)05:04
Global and Local Context Kernels (3)05:24
Local Context Kernel05:32
Branch and bound localization06:28
Efficient Object Localization06:44
Branch & Bound Search - CVPR 2008, PAMI 200907:24
Sets of Rectangles08:08
Branch-Step: Splitting Sets of Boxes08:40
Bounds for Global and Local Context Kernels08:56
Results11:05
Parameter Settings11:08
Results (tabele)11:58
Conclusions (1)13:36
Conclusions (2)13:44
Conclusions (3)13:56
Thanks, Questions?14:24