NDLI: Objects from Animacy: Joint Discovery in Shape and Haar Feature Space

Content Provider	IEEE Xplore Digital Library
Author	Nandi, S. Guha, P. Venkatesh, K.S.
Copyright Year	2008
Description	Author affiliation: Dept. of Electr. Eng., Indian Inst. of Technol., Kanpur (Nandi, S.; Guha, P.; Venkatesh, K.S.)
Abstract	We propose that appearance descriptors derived from the complete animacy of an object during its scene presence more comprehensively capture the essence of an object than descriptors that merely encode uncorrelated sets of its instantaneous appearances. During its frame presence, an object presents itself in many poses with differing frequencies, thus generating multiple modes of varying strengths in the appearance feature space. Further, we utilize tracking information to extract the set of all appearances of the object, while excluding those intervals where the object is partly or fully occluded by other objects or background entities. This allows for completely unsupervised computation of the descriptors that consist of time-indexed vectors from shape and Haar feature templates which are then clustered to obtain appearance modes. These lead to the construction of object-animacy models as probability distributions over the space of co-occurrent shape and Haar templates. These object models are clustered further in an unsupervised manner by using different spatial clustering algorithms with a Bhattacharya distance metric between object models. Unsupervised categorization results on simple (PETS2000) and complex traffic scenes consisting of a wide variety of objects show robust performance of the proposed approach.
Starting Page	730
Ending Page	737
File Size	957533
Page Count	8
File Format	PDF
ISBN	9780769534763
DOI	10.1109/ICVGIP.2008.78
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-12-16
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Computer vision Shape Hierarchical Agglomerative Clustering DBSCAN Probability distribution Template Clustering Object Discovery Haar Feature Space technology Layout Clustering algorithms Object detection Computer graphics Traffic control Robustness
Content Type	Text
Resource Type	Article

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