Object recognition for human behavior analysis

This paper discusses the deformable part-based models for object detection in low contrast images. The objects wheeled walker, walking frame and chair are chosen for the activities walking, sitting and standing. Relationships between detected objects and persons are indicators for those activities. Hence, we enhance a stereo vision system for the purpose of high-level behavior analysis. In order to train models of the objects using the algorithm and get an optimum performance, a sufficient set of images was recorded and annotated. For evaluation, precision and recall curves are reported.

[1]  Gary R. Bradski,et al.  ORB: An efficient alternative to SIFT or SURF , 2011, 2011 International Conference on Computer Vision.

[2]  Gabriela Csurka,et al.  Visual categorization with bags of keypoints , 2002, eccv 2004.

[3]  Mark Everingham,et al.  Shared parts for deformable part-based models , 2011, CVPR 2011.

[4]  Bill Triggs,et al.  Histograms of oriented gradients for human detection , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[5]  Roland Siegwart,et al.  BRISK: Binary Robust invariant scalable keypoints , 2011, 2011 International Conference on Computer Vision.

[6]  Nenghai Yu,et al.  Semantics-preserving bag-of-words models for efficient image annotation , 2009, LS-MMRM '09.

[7]  D. Prasad.  Survey of The Problem of Object Detection In Real Images , 2012 .

[8]  Patrick Boissy,et al.  User-based motion sensing and fuzzy logic for automated fall detection in older adults. , 2007, Telemedicine journal and e-health : the official journal of the American Telemedicine Association.

[9]  Pierre Vandergheynst,et al.  FREAK: Fast Retina Keypoint , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

[10]  Jianliang Tang,et al.  Complete Solution Classification for the Perspective-Three-Point Problem , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[11]  Alexei A. Efros,et al.  How Important Are "Deformable Parts" in the Deformable Parts Model? , 2012, ECCV Workshops.

[12]  Matthijs C. Dorst.  Distinctive Image Features from Scale-Invariant Keypoints , 2011 .

[13]  Xinguo Yu.  Approaches and principles of fall detection for elderly and patient , 2008, HealthCom 2008 - 10th International Conference on e-health Networking, Applications and Services.

[14]  Luc Van Gool,et al.  The Pascal Visual Object Classes (VOC) Challenge , 2010, International Journal of Computer Vision.

[16]  David A. McAllester,et al.  Object Detection with Discriminatively Trained Part Based Models , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[17]  Huiru Zheng,et al.  State of the Art on Night Time Care of People with Dementia , 2009 .