Learn More
Although much progress has been made, current low-level based visual information retrieval technology does not allow users to formulate queries through high-level semantics. More and more digitized art images appear on the Internet, and techniques need to be established on how to organize and retrieve them. In this work, a framework for retrieving art(More)
In this paper, a group-sensitive multiple kernel learning (GS-MKL) method is proposed for object recognition to accommodate the intraclass diversity and the interclass correlation. By introducing the "group" between the object category and individual images as an intermediate representation, GS-MKL attempts to learn group-sensitive multikernel combinations(More)
In this paper, we present a probabilistic multi-task learning approach for visual saliency estimation in video. In our approach, the problem of visual saliency estimation is modeled by simultaneously considering the stimulus-driven and task-related factors in a probabilistic framework. In this framework, a stimulus-driven component simulates the low-level(More)
In the area of image retrieval, post-retrieval processing is often used to refine the retrieval results to better satisfy users' requirements. Previous methods mainly focus on presenting users with relevant results. However, in most cases, users cannot clearly present their requirements by several query words. Therefore, relevant results with rich topic(More)
With the exponential growth of both the amount and diversity of the information that the web encompasses, automatic classification of topic-specific web sites is highly desirable. In this paper we propose a novel approach for web site classification based on the content, structure and context information of web sites. In our approach, the site structure is(More)
With the growing popularity of digitized sports video, automatic analysis of them need be processed to facilitate semantic summarization and retrieval. Playfield plays the fundamental role in automatically analyzing many sports programs. Many semantic clues could be inferred from the results of playfield segmentation. In this paper, a novel playfield(More)
Keyphrases play a key role in text indexing, summariza-tion, and categorization. However, most of the existing keyphrase extraction approaches require human-labeled training sets. In this paper, we propose an automatic key-phrase extraction algorithm using two novel feature weights, which can be used in both supervised and unsu-pervised tasks. This(More)
Content-based video copy detection over large corpus with complex transformations is important but challenging. It is not surprising that most existing methods fall short of either sufficient robustness to detect severely deformed copies or high accuracy to localize copy segments. In this paper, we propose a video copy detection approach which exploits(More)