Object detection using strongly-supervised deformable part models
2012 (English)In: Computer Vision – ECCV 2012: 12th European Conference on Computer Vision, Florence, Italy, October 7-13, 2012, Proceedings, Part I / [ed] Andrew Fitzgibbon, Svetlana Lazebnik, Pietro Perona, Yoichi Sato, Cordelia Schmid, Springer, 2012, no PART 1, 836-849 p.Conference paper (Refereed)
Deformable part-based models [1, 2] achieve state-of-the-art performance for object detection, but rely on heuristic initialization during training due to the optimization of non-convex cost function. This paper investigates limitations of such an initialization and extends earlier methods using additional supervision. We explore strong supervision in terms of annotated object parts and use it to (i) improve model initialization, (ii) optimize model structure, and (iii) handle partial occlusions. Our method is able to deal with sub-optimal and incomplete annotations of object parts and is shown to benefit from semi-supervised learning setups where part-level annotation is provided for a fraction of positive examples only. Experimental results are reported for the detection of six animal classes in PASCAL VOC 2007 and 2010 datasets. We demonstrate significant improvements in detection performance compared to the LSVM  and the Poselet  object detectors.
Place, publisher, year, edition, pages
Springer, 2012. no PART 1, 836-849 p.
, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), ISSN 0302-9743 ; 7572 LNCS
Data sets, Detection performance, Model initialization, Nonconvex cost functions, Object Detection, Object detectors, Partial occlusions, Positive examples, Semi-supervised learning, State-of-the-art performance, Computer vision, Optimization, Supervised learning, Object recognition
Computer Vision and Robotics (Autonomous Systems)
IdentifiersURN: urn:nbn:se:kth:diva-107260DOI: 10.1007/978-3-642-33718-5_60ISI: 000343418300060ScopusID: 2-s2.0-84867871564ISBN: 978-364233717-8OAI: oai:DiVA.org:kth-107260DiVA: diva2:575473
12th European Conference on Computer Vision, ECCV 2012, 7 October 2012 through 13 October 2012, Florence
QC 201212102012-12-102012-12-102016-09-08Bibliographically approved