NDLI: Human parsing using stochastic and-or grammars and rich appearances

Content Provider	IEEE Xplore Digital Library
Author	Rothrock, B. Song-Chun Zhu
Copyright Year	2011
Description	Author affiliation: U.C. Los Angeles, Statistics, USA (Song-Chun Zhu) \|\| U.C. Los Angeles, Computer Science, USA (Rothrock, B.)
Abstract	One of the key challenges to human parsing and pose recovery is handling the variability in geometry and appearance of humans in natural scenes. This variability is due to the large number of distinct articulated configurations, clothing, and self-occlusion, as well as unknown lighting and viewpoint. In this paper, we present a stochastic grammar model that represents the body as an articulated assembly of compositional and reconfigurable parts. The reconfigurable aspect allows a compatible part to be substituted with an alternative part with different attributes, such as for clothing appearance or viewpoint foreshortening. Relations within the grammar enforce consistency between part attributes as well as geometry, allowing a richer set of appearance and geometry constraints over conventional articulated models. Part appearances are modeled by a sparse deformable image template that can still richly describe salient part structures. We describe a dynamic programming parsing algorithm for our model, and show competitive pose recovery results against the state-of-art on a challenging dataset.
Starting Page	640
Ending Page	647
File Size	2748799
Page Count	8
File Format	PDF
ISBN	9781467300629
e-ISBN	9781467300636
DOI	10.1109/ICCVW.2011.6130303
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-11-06
Publisher Place	Spain
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Geometry Legged locomotion Dictionaries Computational modeling Prototypes Production Grammar
Content Type	Text
Resource Type	Article

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