An integrated approach to video retrieval
ADC '08 Proceedings of the nineteenth conference on Australasian database - Volume 75
A Clustering Technique for Video Copy Detection
IbPRIA '07 Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part I
Shot-based video retrieval with optical flow tensor and HMMs
Pattern Recognition Letters
Dynamic video summarization using two-level redundancy detection
Multimedia Tools and Applications
Semantic video fingerprinting and retrieval using face information
Image Communication
Key frame vector and its application to shot retrieval
IMCE '09 Proceedings of the 1st international workshop on Interactive multimedia for consumer electronics
Temporal video structuring for preservation and annotation of video content
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
A fast cube-based video shot retrieval using 3D moment-preserving technique
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Journal of Visual Communication and Image Representation
Video copy detection: sequence matching using hypothesis test
AST/UCMA/ISA/ACN'10 Proceedings of the 2010 international conference on Advances in computer science and information technology
A template-based baseball video scene classification using efficient playfield segmentation
Multimedia Tools and Applications
Pixel-Wise histograms for visual segment description and applications
CIARP'06 Proceedings of the 11th Iberoamerican conference on Progress in Pattern Recognition, Image Analysis and Applications
Caption text and keyframe based video retrieval system
ICCCI'12 Proceedings of the 4th international conference on Computational Collective Intelligence: technologies and applications - Volume Part II
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In this paper, we propose an optimal key frame representation scheme based on global statistics for video shot retrieval. Each pixel in this optimal key frame is constructed by considering the probability of occurrence of those pixels at the corresponding pixel position among the frames in a video shot. Therefore, this constructed key frame is called temporally maximum occurrence frame (TMOF), which is an optimal representation of all the frames in a video shot. The retrieval performance of this representation scheme is further improved by considering the k pixel values with the largest probabilities of occurrence and the highest peaks of the probability distribution of occurrence at each pixel position for a video shot. The corresponding schemes are called k-TMOF and k-pTMOF, respectively. These key frame representation schemes are compared to other histogram-based techniques for video shot representation and retrieval. In the experiments, three video sequences in the MPEG-7 content set were used to evaluate the performances of the different key frame representation schemes. Experimental results show that our proposed representations outperform the alpha-trimmed average histogram for video retrieval.