VORTEX: Video Retrieval and Tracking from Compressed Multimedia Databases—Multiple Object Tracking from MPEG-2 Bit Stream

Schonfeld, Dan; Lelescu, Dan

doi:10.1006/jvci.1999.0432

Cited by 24 publications

(14 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In Fig. 8(a), sample frames show two objects marked by their corresponding tracking frames, which were tracked through the frames of a video shot by the algorithm presented in [3]. Thus, these objects can be extracted and encoded separately using the PCA-based algorithm.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…Content-based video retrieval and indexing [1], [2], [3], [4], has the potential to automate to a large degree the multimedia retrieval process. The objective of such systems is to provide selective access to multimedia data, by finding query-relevant video segments and presenting them to the user.…”

Section: Related Workmentioning

confidence: 99%

“…The object extraction and tracking information, however, is obtained differently depending on the context. For example, for motion-compensated video, objects can be extracted and tracked as presented in [3].…”

Section: Pca-based Representation Of Video Sequencesmentioning

confidence: 99%

“…Thus, we have access to the video shot of interest in compressed form. Additionally, as produced by the other modules of the retrieval system operating on compressed bitstream ( [3], [4]), there exists information regarding the visual changes in the video shot, and objects of interest in the shot. To introduce the algorithm, its functionality is presented for the case of low resolution, frame-level operation.…”

Section: Video Shot Representation In a Multimedia Retrieval Systemmentioning

confidence: 99%

See 3 more Smart Citations

Video Skimming and Summarization Based on Principal Component Analysis

Lelescu¹,

Schonfeld

2001

Management of Multimedia on the Internet

Self Cite

View full text Add to dashboard Cite

Abstract. An increasing number of applications such as content-based multimedia retrieval in a distributed system and low-bitrate video communications, require the efficient processing and transmission of video information. In content-based video retrieval, video segmentation produces video shots characterized by a certain degree of visual cohesiveness. The number of relevant video shots returned by the system can be very large, thereby requiring significant transmission bandwidth. In this paper, we present a new algorithm for the representation of visual information contained in video segments. The approach is based on Principal Component Analysis and takes advantage of the characteristics of the data in video shots, and the optimal energy compaction properties of the transform. The algorithm can use additional information about video sequences provided by a video analysis and retrieval system, such as a visual change estimator, and a video object tracking module.

show abstract

Section: Simulation Resultsmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Pca-based Representation Of Video Sequencesmentioning

confidence: 99%

Section: Video Shot Representation In a Multimedia Retrieval Systemmentioning

confidence: 99%

See 2 more Smart Citations

Video Skimming and Summarization Based on Principal Component Analysis

Lelescu¹,

Schonfeld

2001

Management of Multimedia on the Internet

Self Cite

View full text Add to dashboard Cite

show abstract

“…After segmentation into shots, video indexing can be performed to facilitate a compact representation of information in each video shot, to be used for later retrieval. Algorithms can also perform video analysis or retrieval by tracking specific objects in video shots, as it was presented for example in [1]. In this paper, we propose a new real-time approach for detecting scene changes based on statistical sequential analysis, and operating on minimally-decoded video bitstreams.…”

Section: Introductionmentioning

confidence: 99%

Statistical sequential analysis for real-time video scene change detection on compressed multimedia bitstream

Lelescu¹,

Schonfeld

2003

IEEE Trans. Multimedia

View full text Add to dashboard Cite

Abstract-The increased availability and usage of multimedia information have created a critical need for efficient multimedia processing algorithms. These algorithms must offer capabilities related to browsing, indexing, and retrieval of relevant data. A crucial step in multimedia processing is that of reliable video segmentation into visually coherent video shots through scene change detection. Video segmentation enables subsequent processing operations on video shots, such as video indexing, semantic representation, or tracking of selected video information. Since video sequences generally contain both abrupt and gradual scene changes, video segmentation algorithms must be able to detect a large variety of changes. While existing algorithms perform relatively well for detecting abrupt transitions (video cuts), reliable detection of gradual changes is much more difficult. In this paper, a novel one-pass, real-time approach to video scene change detection based on statistical sequential analysis and operating on compressed multimedia bitstream is proposed. Our approach models video sequences as stochastic processes, with scene changes being reflected by changes in the characteristics (parameters) of the process. Statistical sequential analysis is used to provide an unified framework for the detection of both abrupt and gradual scene changes.

show abstract