In this paper, we specifically propose the Weber-Fechner Law-based human attention model for semantic scene analysis in movies. Different from traditional video processing techniq...
Anan Liu, Yongdong Zhang, Yan Song, Dongming Zhang...
We address the problem of localizing and obtaining high-resolution footage of the people present in a scene. We propose a biologically-inspired solution combining pre-attentive, lo...
James H. Elder, Simon J. D. Prince, Yuqian Hou, Mi...
This paper presents a method for movie genre categorization of movie trailers, based on scene categorization. We view our approach as a step forward from using only low-level visu...
Howard Zhou, Tucker Hermans, Asmita V. Karandikar,...
This paper exploits the context of natural dynamic scenes
for human action recognition in video. Human actions
are frequently constrained by the purpose and the physical
propert...
Marcin Marszalek (INRIA), Ivan Laptev (INRIA), Cor...
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...