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https://doi.org/10.1109/cvpr.2...
Article . 2005 . Peer-reviewed
Data sources: Crossref
https://doi.org/10.1109/cvpr.2...
Article . 2005 . Peer-reviewed
Data sources: Crossref
DBLP
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DBLP
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Tracking Multiple Objects through Occlusions

Authors: Yan Huang 0017; Irfan A. Essa;

Tracking Multiple Objects through Occlusions

Abstract

Visual tracking of multiple objects with continuous interactions is important for many applications such as surveillance and effective user interfaces. Complex interactions between objects results in both temporally and spatially significant occlusions, making multi-object tracking a challenging problem. We present an approach for tracking varying number of objects through significant occlusions. Our approach builds on the idea of object permanence. That is, partially or fully occluded objects, even though not observable, still exist in the close proximity of their occluders. To demonstrate the viability of this approach, we have concentrated on tracking hands and objects as a person interacts with multiple objects on a desktop. We experimented with 5 indoor video sequences and present the results of two representative ones: lego sequence and shell game.

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    popularity
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    influence
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
24
Top 10%
Top 10%
Average