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Shadow Detection by Integrating Multiple Features

Authors: Kuo-Hua Lo; Mau-Tsuen Yang;

Shadow Detection by Integrating Multiple Features

Abstract

Cast shadows of moving foreground objects in a scene often result in problems for many applications such as surveillance, object tracking/recognition, video content analysis and intelligent transportation systems. In this paper we presented an algorithm exploiting information of color, shading, texture, neighborhoods and temporal consistency to detect shadows in a scene efficiently and reliably. The experimental results showed that the proposed method can detect umbra as well as penumbra in different kinds of scenarios under various illumination conditions.

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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!
4
Average
Average
Average
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