Adaptive Edge-Oriented Shot Boundary Detection

We study the problem of video shot boundary detection using an adaptive edge-oriented framework. Our approach is distinct in its use of multiple multilevel features in the required processing. Adaptation is provided by a careful analysis of these multilevel features, based on shot variability. We consider three levels of adaptation: at the feature extraction stage using locally-adaptive edge maps, at the video sequence level, and at the individual shot level. We show how to provide adaptive parameters for the multilevel edge-based approach, and how to determine adaptive thresholds for the shot boundaries based on the characteristics of the particular shot being indexed. The result is a fast adaptive scheme that provides a slightly better performance in terms of robustness, and a five fold efficiency improvement in shot characterization and classification. The reported work has applications beyond direct video indexing, and could be used in real-time applications, such as in dynamic monitoring and modeling of video data traffic in multimedia communications, and in real-time video surveillance. Experimental results are included

Pattern matching in compressed texts and images

Surveys techniques that solve the two basic problems of efficiency (in storage and computation) at the same time. It also compares and contrasts methods that have been proposed for compression, and for compressed pattern matching in text and images. It examines compressed pattern matching for both lossy compression and lossless compression

Pattern Matching in Compressed Text and Images

Normally compressed data needs to be decompressed before it is processed, but if the compression has been done in the fight way, it is often possible to search the data without having to decompress it, or at least only partially decompress it. The problem can be divided into lossless and lossy compression methods, and then in each of these cases the pattern matching can be either exact or inexact. Much work has been reported in the literature on techniques for all of these cases, including algorithms that are suitable for pattern matching for various compression methods, and compression methods designed specifically for pattern matching. This work is surveyed in this paper. The paper also exposes the important relationship between pattern matching and compression, and proposes some performance measures for compressed pattern matching algorithms. Ideas and directions for future work are also described

Approximate Pattern Matching Using The Burrows-Wheeler Transform

Summary form only given. The approximate pattern matching on the text transformed by the Burrows-Wheeler transform (BWT) was considered. This is an important first step towards developing a compressed pattern matching algorithm for the BWT based compression system. Algorithms are proposed to solve the K-mismatch problem. Tests were performed on different pattern lengths using 133 selected files from the Canterbury, Calgary, and TREC corpus. The results on the K-mismatch pattern matching show that the running time and storage are superior to the fast suffix tree approach. Thus, once the index arrays are created, for repeated pattern search operations and for long patterns, the proposed algorithms perform significantly better than the agrep and ngrep. Using DFA verification, the search time is almost constant. The amortized cost is lower for multiple patterns search operations

Adaptive Edge-Oriented Shot Boundary Detection

We study the problem of video shot boundary detection using an adaptive edge-oriented framework. Our approach is distinct in its use of multiple multilevel features in the required processing. Adaptation is provided by a careful analysis of these multilevel features, based on shot variability. We consider three levels of adaptation: at the feature extraction stage using locally-adaptive edge maps, at the video sequence level, and at the individual shot level. We show how to provide adaptive parameters for the multilevel edge-based approach, and how to determine adaptive thresholds for the shot boundaries based on the characteristics of the particular shot being indexed. The result is a fast adaptive scheme that provides a slightly better performance in terms of robustness, and a five fold efficiency improvement in shot characterization and classification. The reported work has applications beyond direct video indexing, and could be used in real-time applications, such as in dynamic monitoring and modeling of video data traffic in multimedia communications, and in real-time video surveillance. Experimental results are included.</p