A new paradigm for analysis of MPEG compressed videos
Journal of Network and Computer Applications
Automatic Cut Detection in MPEG Movies: A Multi-expert Approach
Proceedings of the Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition
Automatic Closed Caption Detection and Font Size Differentiation in MPEG Video
VISUAL '02 Proceedings of the 5th International Conference on Recent Advances in Visual Information Systems
Motion Activity Based Shot Identification and Closed Caption Detection for Video Structuring
VISUAL '02 Proceedings of the 5th International Conference on Recent Advances in Visual Information Systems
A Robust, Efficient, and Fast Global Motion Estimation Method from MPEG Compressed Video
PCM '02 Proceedings of the Third IEEE Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
Independent motion detection directly from compressed surveillance video
IWVS '03 First ACM SIGMM international workshop on Video surveillance
Object Level Frame Comparison for Video Shot Detection
WACV-MOTION '05 Proceedings of the IEEE Workshop on Motion and Video Computing (WACV/MOTION'05) - Volume 2 - Volume 02
Direct feature detection on compressed images
Pattern Recognition Letters
Fast and efficient method for block edge classification
Proceedings of the 2006 international conference on Wireless communications and mobile computing
Temporal segmentation of MPEG video streams
EURASIP Journal on Applied Signal Processing
A holistic, in-compression approach to video segmentation for independent motion detection
EURASIP Journal on Advances in Signal Processing
AEE'07 Proceedings of the 6th conference on Applications of electrical engineering
Adaptive edge-oriented shot boundary detection
Journal on Image and Video Processing
Video watermarking based on scene detection and 3D DFT
CSS '07 Proceedings of the Fifth IASTED International Conference on Circuits, Signals and Systems
Content-based story segmentation of news video by multimodal analysis
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 7
A low complexity motion segmentation based on semantic representation of encoded video streams
ICIAP'11 Proceedings of the 16th international conference on Image analysis and processing - Volume Part II
An extended-HCT semantic description for visual place recognition
International Journal of Robotics Research
DCT-Domain image retrieval via block-edge-patterns
ICIAR'06 Proceedings of the Third international conference on Image Analysis and Recognition - Volume Part I
The segmentation of news video into story units
WAIM'05 Proceedings of the 6th international conference on Advances in Web-Age Information Management
Rapid cut detection on compressed video
CIARP'11 Proceedings of the 16th Iberoamerican Congress conference on Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
Intelligent copyright protection system using a matching video retrieval algorithm
Multimedia Tools and Applications
Multi-cue based place learning for mobile robot navigation
AIS'12 Proceedings of the Third international conference on Autonomous and Intelligent Systems
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In order to process video data efficiently, a video segmentation technique through scene change detection must be required. This is a fundamental operation used in many digital video applications such as digital libraries, video on demand (VOD), etc. Many of these advanced video applications require manipulations of compressed video signals. So, the scene change detection process is achieved by analyzing the video directly in the compressed domain, thereby avoiding the overhead of decompressing video into individual frames in the pixel domain. In this paper, we propose a fast scene change detection algorithm using direct feature extraction from MPEG compressed videos, and evaluate this technique using sample video data, First, we derive binary edge maps from the AC coefficients in blocks which were discrete cosine transformed. Second, we measure edge orientation, strength and offset using correlation between the AC coefficients in the derived binary edge maps. Finally, we match two consecutive frames using these two features (edge orientation and strength). This process was made possible by a new mathematical formulation for deriving the edge information directly from the discrete cosine transform (DCT) coefficients. We have shown that the proposed algorithm is faster or more accurate than the previously known scene change detection algorithms