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Unified crowd segmentation

Abstract:

This paper presents a unified approach to crowd segmentation. A global solution is generated using an Expectation Maximization framework. Initially, a head and shoulder detector is used to nominate an exhaustive set of person locations and these form the person hypotheses. The image is then partitioned into a grid of small patches which are each assigned to one of the person hypotheses. A key idea of this paper is that while whole body monolithic person detectors can fail due to occlusion, a ...

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Institution:
University of Oxford
Department:
Oxford, MPLS, Clinical Medicine, Biomedical Research Centre
Role:
Author
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Journal:
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume:
5305 LNCS
Issue:
PART 4
Pages:
691-704
Publication date:
2008-01-01
DOI:
EISSN:
1611-3349
ISSN:
0302-9743
URN:
uuid:aa0cec1a-d46b-49dc-b6ae-83ebd556dd4a
Source identifiers:
439055
Local pid:
pubs:439055
Language:
English

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