A feature-based algorithm for detecting and classifying scene breaks
Proceedings of the third ACM international conference on Multimedia
ASSERT: a physician-in-the-loop content-based retrieval system for HRCT image databases
Computer Vision and Image Understanding - Special issue on content-based access for image and video libraries
Medical Image Analysis: Progress over Two Decades and the Challenges Ahead
IEEE Transactions on Pattern Analysis and Machine Intelligence
Modeling Dynamic Objects in Video Databases: A Logic Based Approach
ER '01 Proceedings of the 20th International Conference on Conceptual Modeling: Conceptual Modeling
A visual search system for video and image databases
ICMCS '97 Proceedings of the 1997 International Conference on Multimedia Computing and Systems
Automatic view recognition in echocardiogram videos using parts-based representation
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Evaluation of automatic shot boundary detection on a large video test suite
IM'99 Proceedings of the 1999 international conference on Challenge of Image Retrieval
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In this work we propose a hierarchical state-based model for representing an echocardiogram video using objects present and their dynamic behavior. The modeling is done on the basis of the different types of views like short axis view, long axis view, apical view, etc. For view classification, an artificial neural network is trained with the histogram of a ‘region of interest' of each video frame. A state transition diagram is used to represent the states of objects in different views and corresponding transition from one state to another. States are detected with the help of synthetic M-mode images. In contrast to traditional single M-mode approach, we propose a new approach named as ‘Sweep M-mode' for the detection of states.