The semi-explicit shape model for multi-object detection and classification

Authors:
Simon Polak;Amnon Shashua
Affiliations:
School of Computer Science and Engineering, The Hebrew University of Jerusalem;School of Computer Science and Engineering, The Hebrew University of Jerusalem
Venue:
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part II
Year:
2010

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Abstract

We propose a model for classification and detection of object classes where the number of classes may be large and where multiple instances of object classes may be present in an image. The algorithm combines a bottom-up, low-level, procedure of a bag-of-words naive Bayes phase for winnowing out unlikely object classes with a high-level procedure for detection and classification. The high-level process is a hybrid of a voting method where votes are filtered using beliefs computed by a class-specific graphical model. In that sense, shape is both explicit (determining the voting pattern) and implicit (each object part votes independently) -- hence the term "semi-explicit shape model".