Occlusion Reasoning for Object De-tection under Arbitrary Viewpoint
CVPR 2012Edward Hsiao and Martial Herbert
Presenter : Byungju Kim
Overview
• Problem setting• Texture-less Object Detector• Main Idea• Experiment result• Conclusion
Assumption
• Arbitrary viewpoint• Household environment– Kitchen
• Occluder is on same support plane
Why occlusion problem?
Let’s find scissors in the pic-tures
Texture-less Object
Texture-less Object Detector
• LINE2D
Texture-less Object Detector
• LINE2D
Scoring
Z : detection windowN : number of points = 0 if the point i is occluded 1 if the point i is visible
Penalty term
Occlusion prior
𝑉 𝑖
Occlusion Conditional Likelihood
Scoring
Experiment Result
Experiment Result
Conclusion
• Calibration for multi-view is necessary• Not scale-invariant
• Idea is adaptable for different environ-ment
• Textured object could perform better
Thank you
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