A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Statistics: principles and methods
Statistics: principles and methods
International Journal of Computer Vision
An introduction to wavelets
Quad-tree segmentation for texture-based image query
MULTIMEDIA '94 Proceedings of the second ACM international conference on Multimedia
Fast multiresolution image querying
SIGGRAPH '95 Proceedings of the 22nd annual conference on Computer graphics and interactive techniques
Texture Features for Browsing and Retrieval of Image Data
IEEE Transactions on Pattern Analysis and Machine Intelligence
Wavelets for computer graphics: theory and applications
Wavelets for computer graphics: theory and applications
A texture thesaurus for browsing large aerial photographs
Journal of the American Society for Information Science - Special topic issue: artificial intelligence techniques for emerging information systems applications
Color and spatial feature for content-based image retrieval
Pattern Recognition Letters
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fast wavelet histogram techniques for image indexing
Computer Vision and Image Understanding - Special issue on content-based access for image and video libraries
Image matching using run-length feature
Pattern Recognition Letters - Special issue on image/video indexing and retrieval
Learning Similarity Matching in Multimedia Content-Based Retrieval
IEEE Transactions on Knowledge and Data Engineering
Multimedia Systems - Special section on video libraries
Non-parametric Similarity Measures for Unsupervised Texture Segmentation and Image Retrieval
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Efficient Retrieval by Shape Content
ICMCS '99 Proceedings of the IEEE International Conference on Multimedia Computing and Systems - Volume 2
Effective Image Retrival Using Deformable Templates
ICPR '96 Proceedings of the International Conference on Pattern Recognition (ICPR '96) Volume III-Volume 7276 - Volume 7276
A Metric for Distributions with Applications to Image Databases
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Matching and Retrieval Based on the Vocabulary and Grammar of Color Patterns
ICMCS '99 Proceedings of the IEEE International Conference on Multimedia Computing and Systems - Volume 2
Detection of similar sequences in EEG maps series using correlation coefficients matrix
Machine Graphics & Vision International Journal
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Comparison of video sequences is an important operation in many multimedia information systems. The similarity measure for comparison is typically based on some measure of correlation with the perceptual similarity (or difference) amongst the video sequences or with the similarity (or difference) in some measure of semantics associated with the video sequences. In content-based similarity analysis, the video data are expressed in terms of different features. Similarity matching is then performed by quantifying the feature relationships between the target video and query video shots, with either an individual feature or with a feature combination. In this study, two approaches are proposed for the similarity analysis of video shots. In the first approach, mosaic images are created from video shots, and the similarity analysis is done by determining the similarities amongst the mosaic images. In the second approach, key frames are extracted for each video shot and the similarity amongst video shots is determined by comparing the key frames of the video shots. The features extracted include image histograms, slopes, edges, and wavelets. Both individual features and feature combinations are used in similarity matching using an artificial neural network. The similarity rank of the query video shots is determined based on the values of the coefficients of determination and the mean absolute error. The study reported in this paper shows that the mosaic-based similarity analysis can be expected to yield a more reliable result, whereas the key frame-based similarity analysis could be potentially applied to a wider range of applications. The weighted non-linear feature combination is shown to yield better results than a single feature for video similarity analysis. The coefficient of determination is shown to be a better criterion than the mean absolute error in similarity matching analysis.