Temporal Segmentation of MPEG Video Streams
- PDF / 639,964 Bytes
- 5 Pages / 600 x 792 pts Page_size
- 61 Downloads / 169 Views
Temporal Segmentation of MPEG Video Streams Janko Calic Multimedia and Vision Research Lab, Department of Electronic Engineering, Queen Mary, University of London, Mile End Road, London E1 4NS, UK Email: [email protected]
Ebroul Izquierdo Multimedia and Vision Research Lab, Department of Electronic Engineering, Queen Mary, University of London, Mile End Road, London E1 4NS, UK Email: [email protected] Received 30 July 2001 and in revised form 9 February 2002 Many algorithms for temporal video partitioning rely on the analysis of uncompressed video features. Since the information relevant to the partitioning process can be extracted directly from the MPEG compressed stream, higher efficiency can be achieved utilizing information from the MPEG compressed domain. This paper introduces a real-time algorithm for scene change detection that analyses the statistics of the macroblock features extracted directly from the MPEG stream. A method for extraction of the continuous frame difference that transforms the 3D video stream into a 1D curve is presented. This transform is then further employed to extract temporal units within the analysed video sequence. Results of computer simulations are reported. Keywords and phrases: shot detection, video indexing, compressed domain, MPEG stream.
1.
INTRODUCTION
The development of highly efficient video compression technology combined with the rapid increase in desktop computer performance, and a decrease in the storage cost, have led to a proliferation of digital video media. As a consequence, many terabytes of video data stored in large video databases, are often not catalogued and are accessible only by the sequential scanning of the sequences. To make the use of large video databases more efficient, we need to be able to automatically index, search, and retrieve relevant material. It is important to stress that even by using the leading edge hardware accelerators, factors such as algorithm complexity and storage capacity are concerns that still must be addressed. For example, although compression provides tremendous space savings, it can often introduce processing inefficiencies when decompression is required to perform spatial processing for indexing and retrieval. With this in mind, one of the initial considerations in development of a system for video retrieval is an attempt to enhance access capabilities within the existing compression representations. Since the identification of the temporal structures of video is an essential task of video indexing and retrieval [1], shot detection has been generally accepted to be a first step in the indexing algorithm implementation. We define a shot as a sequence of frames that were (or appear to be) “continuously captured from the same camera” [2]. A scene is defined
as a “collection of one or more adjoining shots that focus on an object or objects of interest” [3]. Shot change detection algorithms can be classified, according to the features used for processing, into uncompressed and compressed domain algorithms. Algo
Data Loading...
