Motion detection and estimation are known to be important in many automated surveillance systems. It has drawn significant research interest in the field of computer vision. This ...
This paper presents a new model of human attention that allows salient areas to be extracted from video frames. As automatic understanding of video semantic content is still far fr...
— We present a hardware-accelerated implementation of a bottom-up visual attention algorithm. This algorithm generates a multi-scale saliency map from differences in image intens...
Detection of moving objects in video streams is the first relevant step of information extraction in many computer vision applications. Aside from the intrinsic usefulness of being...
We introduce a new task-independent framework to model top-down overt visual attention based on graphical models for probabilistic inference and reasoning. We describe a Dynamic B...