Algorithms for clustering data
Algorithms for clustering data
Introduction to statistical pattern recognition (2nd ed.)
Introduction to statistical pattern recognition (2nd ed.)
Automatic partitioning of full-motion video
Multimedia Systems
Motion recovery for video content classification
ACM Transactions on Information Systems (TOIS) - Special issue on video information retrieval
Retrieving and visualizing video
Communications of the ACM
An eigenspace update algorithm for image analysis
Graphical Models and Image Processing
Segmentation of video by clustering and graph analysis
Computer Vision and Image Understanding
A Distributed Algorithm for Content Based Indexing of Images by Projections on Ritz Primary Images
Data Mining and Knowledge Discovery
IEEE Transactions on Pattern Analysis and Machine Intelligence
Normalized Cuts and Image Segmentation
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Some Extensions of the K-Means Algorithm for Image Segmentation and Pattern Classification
Some Extensions of the K-Means Algorithm for Image Segmentation and Pattern Classification
Video query: research directions
IBM Journal of Research and Development - Papers on mustimedia systems
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The content-plot of a video clip is created by positioning several key frames in two-dimensions and connecting them with lines. It is constructed so that it should be possible to follow the events shown in the video by moving along the lines. Content plots were previously computed by clustering together frames that are contiguous in time. We propose to cluster together frames if they are related by a short chain of similarly looking frames even if they are not adjacent on the time-line. The computational problem can be formulated as a graph clustering problem that we solve by extending the classic k-means technique to graphs. This new graph clustering algorithm is the main technical contribution of this paper.