Powered by OpenAIRE graph
Found an issue? Give us feedback
addClaim

Probability Estimation for People Detection.

Authors: Sun, Qingjie; Wu, Enhua;

Probability Estimation for People Detection.

Abstract

This paper presents a probability method for detecting people in a static image. We simplify people as a torso and four limbs. The torso is fitted by a quadrangle, and each limb is fitted by one or two quadrangles depending on its pose. In order to find people, we should try to find a combination of quadrangles that must satisfy some geometric and topological constrains. Firstly, we try to detect and fit rectangle regions in the image, then we search some combinations of rectangles under certain constrains. After we get a combination, we calculate its probability of being people. If the probability is above threshold, we adjust the vertexes of rectangles so as to get a compact people model.

Country
Czech Republic
Keywords

segmentace obrazu, detekce osob, people detection, image segmentation

  • BIP!
    Impact byBIP!
    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).
    0
    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.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
Powered by OpenAIRE graph
Found an issue? Give us feedback
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!
0
Average
Average
Average
Green