Algorithms for clustering data
Algorithms for clustering data
Creating full view panoramic image mosaics and environment maps
Proceedings of the 24th annual conference on Computer graphics and interactive techniques
Automatic detection of 'Goal' segments in basketball videos
MULTIMEDIA '01 Proceedings of the ninth ACM international conference on Multimedia
Digital Image Processing
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
A Spatiotemporal Motion Model for Video Summarization
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Video Scene Segmentation via Continuous Video Coherence
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Mosaic based representations of video sequences and their applications
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Efficient matching and clustering of video shots
ICIP '95 Proceedings of the 1995 International Conference on Image Processing (Vol. 1)-Volume 1 - Volume 1
Time-Constrained Clustering for Segmentation of Video into Story Unites
ICPR '96 Proceedings of the International Conference on Pattern Recognition (ICPR '96) Volume III-Volume 7276 - Volume 7276
Automated high-level movie segmentation for advanced video-retrieval systems
IEEE Transactions on Circuits and Systems for Video Technology
Automated location matching in movies
Computer Vision and Image Understanding - Special isssue on video retrieval and summarization
Proceedings of the 6th ACM SIGMM international workshop on Multimedia information retrieval
Browsing personal media archives with spatial context using panoramas
MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
Video abstraction: A systematic review and classification
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Segmenting, Modeling, and Matching Video Clips Containing Multiple Moving Objects
IEEE Transactions on Pattern Analysis and Machine Intelligence
EURASIP Journal on Applied Signal Processing
Structure and event mining in sports video with efficient mosaic
Multimedia Tools and Applications
Video scene segmentation and semantic representation using a novel scheme
Multimedia Tools and Applications
Places clustering of full-length film key-framesusing latent aspect modeling over SIFT matches
IEEE Transactions on Circuits and Systems for Video Technology
Automatic generation of conference video proceedings
Journal of Visual Communication and Image Representation
Multimedia content analysis: the next wave
CIVR'03 Proceedings of the 2nd international conference on Image and video retrieval
ACM SIGGRAPH 2010 papers
Segmenting, modeling, and matching video clips containing multiple moving objects
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
High level video temporal segmentation
ISVC'11 Proceedings of the 7th international conference on Advances in visual computing - Volume Part I
Efficient visual content retrieval and mining in videos
PCM'04 Proceedings of the 5th Pacific Rim Conference on Advances in Multimedia Information Processing - Volume Part II
Video summarization: techniques and classification
ICCVG'12 Proceedings of the 2012 international conference on Computer Vision and Graphics
Video Segmentation and Structuring for Indexing Applications
International Journal of Multimedia Data Engineering & Management
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We present an approach for compact video summaries that allows fast and direct access to video data. The video is segmented into shots and, in appropriate video genres, into scenes, using previously proposed methods. A new concept that supports the hierarchical representation of video is presented, and is based on physical setting and camera locations. We use mosaics to represent and cluster shots, and detect appropriate mosaics to represent scenes. In contrast to approaches to video indexing which are based on key-frames, our efficient mosaic-based scene representation allows fast clustering of scenes into physical settings, as well as further comparison of physical settings across videos. This enables us to detect plots of different episodes in situation comedies and serves as a basis for indexing whole video sequences. In sports videos where settings are not as well defined, our approachallo ws classifying shots for characteristic event detection. We use a novel method for mosaic comparison and create a highly compact non-temporal representation of video. This representation allows accurate comparison of scenes across different videos and serves as a basis for indexing video libraries.