Learn More
|Content-Based Image Retrieval (CBIR) has become one of the most active research areas in the past few years. Many visual feature representations have been explored and many systems built. While these research e orts establish the basis of CBIR, the usefulness of the proposed approaches is limited. Speci cally, these e orts have relatively ignored two(More)
This paper provides a comprehensive survey of the technical achievements in the research area of image retrieval, especially content-based image retrieval, an area that has been so active and prosperous in the past few years. The survey includes 100+ papers covering the research aspects of image feature representation and extraction, multidimensional(More)
Technology advances in the areas of Image processing IP and Information Retrieval IR have evolved separately for a long time However successful content based image retrieval systems require the integration of the two There is an urgent need to develop integration mechanisms to link the image retrieval model to text retrieval model such that the well(More)
Combining learning with vision techniques in interactive image retrieval has been an active research topic during the past few years. However, existing learning techniques either are based on heuristics or fail to analyze the working conditions. Furthermore, there is almost no in depth study on how to effectively learn from the users when there are multiple(More)
| Content-Based Image Retrieval (CBIR) has become one of the most active research areas in the past few years. Many visual feature representations have been explored and many systems built. While these research eeorts establish the basis of CBIR, the usefulness of the proposed approaches is limited. Speciically, these eeorts have relatively ignored two(More)
Point-of-Interest (POI) recommendation has become an important means to help people discover attractive locations. However, extreme sparsity of user-POI matrices creates a severe challenge. To cope with this challenge, viewing mobility records on location-based social networks (LBSNs) as implicit feedback for POI recommendation, we first propose to exploit(More)
A fundamental task in video analysis is to extract structures from the video to facilitate user's access (browsing and retrieval). Motivated by the important role that the table of content (ToC) plays in a book, in this paper, we introduce the concept of ToC in the video domain. Some existing approaches implicitly use the ToC, but are mainly limited to(More)
In today's fast-paced world, while the number of channels of television programming available is increasing rapidly, the time available to watch them remains the same or is decreasing. Users desire the capability to watch the programs time-shifted (on-demand) and/or to watch just the highlights to save time. In this paper we explore how to provide for the(More)
Tracking objects involves the modeling of non-linear nonGaussian systems. On one hand, variants of Kalman filters are limited by their Gaussian assumptions. On the other hand, conventional particle filter, e.g., CONDENSATION, uses transition prior as the proposal distribution. The transition prior does not take into account current observation data, and(More)
Automatically describing video content with natural language is a fundamental challenge of computer vision. Re-current Neural Networks (RNNs), which models sequence dynamics, has attracted increasing attention on visual interpretation. However, most existing approaches generate a word locally with the given previous words and the visual content, while the(More)