Learn More
Traditional video coding and streaming algorithms do not been fully utilized in content information of video in bit allocation and adaptation. This paper proposes a content-based video streaming method based on visual attention model to better utilize network bandwidth and achieve better subjective video quality. First, visual attention model is exploited(More)
Recently the research on supervised term weighting has attracted growing attention in the field of Traditional Text Categorization (TTC) and Sentiment Analysis (SA). Despite their impressive achievements, we show that existing methods more or less suffer from the problem of over-weighting. Overlooked by prior studies, over-weighting is a new concept(More)
Web content structure is proposed to facilitate automatic web page adaptation in this paper. By identifying the logic relationship of web content based on layout information, web content structure effectively represents au-thors' presentation intention. An automatic top-down, tag-tree independent approach to detect web content structure is presented. It(More)
This paper presents a principled and practical method for the computation of visual saliency of spatiotemporal events in full motion videos. Based on the assumption that uniqueness or informative-ness correlates with saliency, our model predicts the saliency of a spatiotemporal event based on the information it contains. To compute the uniqueness of the(More)
This paper introduces an approach for image shadow removal by using pulse coupled neural network (PCNN), based on the phenomena of synchronous pulse bursts in the animal visual cortexes. Two shadow-removing criteria are proposed. These two criteria decide how to choose the optimal parameter (the linking strength beta). The computer simulation results of(More)