Showing papers by "Yap-Peng Tan published in 1997"
TL;DR: A basketball annotation system which combines the low-level information extracted from MPEG stream with the prior knowledge of basketball video structure to provide high level content analysis, annotation and browsing for events such as wide- angle and close-up views, fast breaks, steals, potential shots, number of possessions and possession times is developed.
Abstract: Automated analysis and annotation of video sequences are important for digital video libraries, content-based video browsing and data mining projects. A successful video annotation system should provide users with useful video content summary in a reasonable processing time. Given the wide variety of video genres available today, automatically extracting meaningful video content for annotation still remains hard by using current available techniques. However, a wide range video has inherent structure such that some prior knowledge about the video content can be exploited to improve our understanding of the high-level video semantic content. In this paper, we develop tools and techniques for analyzing structured video by using the low-level information available directly from MPEG compressed video. Being able to work directly in the video compressed domain can greatly reduce the processing time and enhance storage efficiency. As a testbed, we have developed a basketball annotation system which combines the low-level information extracted from MPEG stream with the prior knowledge of basketball video structure to provide high level content analysis, annotation and browsing for events such as wide- angle and close-up views, fast breaks, steals, potential shots, number of possessions and possession times. We expect our approach can also be extended to structured video in other domains.© (1997) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.
142 citations
TL;DR: It is shown that by intelligently combining unequal channel protection and source detection, both subjectively and objectively better quality of reconstructed images can be obtained.
Abstract: One way to efficiently combat channel errors is to employ unequal error protection (UEP) for information of different importance. The traditional approach to UEP through channel coding does not fully take advantage of the image signal properties. The high correlation nature of the image signal makes it possible to detect and correct many channel errors directly on the decoded image. Based on this observation, we propose in this paper a new approach which provides UEP through channel coding in a way seemingly contrast to traditional ones. Specifically, some good source detection/correction schemes are incorporated to detect/correct, directly on the decoded image, the noticeable damage which is often caused by channel errors affecting the important (in the view of tradition UEP schemes) data. With the help of source detectors, the problem of how to prioritize the transmitted data for channel protection is revisited and reformulated. We show that by intelligently combining unequal channel protection and source detection, both subjectively and objectively better quality of reconstructed images can be obtained. A general framework of the new approach is presented. Three case studies, including one for transmission of vector quantized images over noisy channels, one for a simplified fax coding system and the other one suggested by an intelligent block dropping approach, are examined.
3 citations