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» Motion Detection using a Model of Visual Attention
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CVPR
2006
IEEE
15 years 7 months ago
Learning Joint Top-Down and Bottom-up Processes for 3D Visual Inference
We present an algorithm for jointly learning a consistent bidirectional generative-recognition model that combines top-down and bottom-up processing for monocular 3d human motion ...
Cristian Sminchisescu, Atul Kanaujia, Dimitris N. ...
ICMCS
2008
IEEE
141views Multimedia» more  ICMCS 2008»
15 years 8 months ago
Visual focus of attention estimation from head pose posterior probability distributions
We address the problem of recognizing the visual focus of attention (VFOA) of meeting participants from their head pose and contextual cues. The main contribution of the paper is ...
Sileye O. Ba, Jean-Marc Odobez
118
Voted
BMVC
2001
15 years 4 months ago
Adaptive Visual System for Tracking Low Resolution Colour Targets
This paper addresses the problem of using appearance and motion models in classifying and tracking objects when detailed information of the object’s appearance is not available....
Pakorn KaewTrakulPong, Richard Bowden
119
Voted
BC
1999
94views more  BC 1999»
15 years 1 months ago
Speed tuning in elementary motion detectors of the correlation type
A prominent model of visual motion detection is the so-called correlation or Reichardt detector. Whereas this model can account for many properties of motion vision, from humans to...
Johannes M. Zanker, M. V. Srinivasan, Martin Egelh...
CVPR
2008
IEEE
16 years 3 months ago
Spatio-temporal Saliency detection using phase spectrum of quaternion fourier transform
Salient areas in natural scenes are generally regarded as the candidates of attention focus in human eyes, which is the key stage in object detection. In computer vision, many mod...
Chenlei Guo, Qi Ma, Liming Zhang