• Publication
  • PrePrints
  • Abstract - Occlusion Reasoning for Object Detection under Arbitrary Viewpoint
 This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
Occlusion Reasoning for Object Detection under Arbitrary Viewpoint
PrePrint
ISSN: 0162-8828
We present a unified occlusion model for object instance detection under arbitrary viewpoint.Whereas previous approaches primarily modeled local coherency of occlusions or attempted to learn the structure of occlusions from data, we propose to explicitly model occlusions by reasoning about 3D interactions of objects. Our approach accurately represents occlusions under arbitrary viewpoint without requiring additional training data, which can often be difficult to obtain. We validate our model by incorporating occlusion reasoning with the state-of-the-art LINE2D and Gradient Network methods for object instance detection and demonstrate significant improvement in recognizing texture-less objects under severe occlusions.
Citation:
Martial Hebert, "Occlusion Reasoning for Object Detection under Arbitrary Viewpoint," IEEE Transactions on Pattern Analysis and Machine Intelligence, 04 Feb. 2014. IEEE computer Society Digital Library. IEEE Computer Society, <http://doi.ieeecomputersociety.org/10.1109/TPAMI.2014.2303085>
Usage of this product signifies your acceptance of the Terms of Use.