Video parsing, retrieval and browsing: an integrated and content-based solution
Proceedings of the third ACM international conference on Multimedia
Communications of the ACM
A graph distance metric based on the maximal common subgraph
Pattern Recognition Letters
Time-compression: systems concerns, usage, and benefits
Proceedings of the SIGCHI conference on Human Factors in Computing Systems
Abstracting home video automatically
MULTIMEDIA '99 Proceedings of the seventh ACM international conference on Multimedia (Part 2)
Efficient and cost-effective techniques for browsing and indexing large video databases
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
An integrated scheme for object-based video abstraction
MULTIMEDIA '00 Proceedings of the eighth ACM international conference on Multimedia
Key-frame extraction and shot retrieval using nearest feature line (NFL)
MULTIMEDIA '00 Proceedings of the 2000 ACM workshops on Multimedia
On clustering and retrieval of video shots
MULTIMEDIA '01 Proceedings of the ninth ACM international conference on Multimedia
Mean Shift: A Robust Approach Toward Feature Space Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Entropy metrics used for video summarization
SCCG '02 Proceedings of the 18th spring conference on Computer graphics
Automatic Video Database Indexing and Retrieval
Multimedia Tools and Applications
A Comparison of Algorithms for Maximum Common Subgraph on Randomly Connected Graphs
Proceedings of the Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition
Video Skimming and Characterization through the Combination of Image and Language Understanding
CAIVD '98 Proceedings of the 1998 International Workshop on Content-Based Access of Image and Video Databases (CAIVD '98)
A visual search system for video and image databases
ICMCS '97 Proceedings of the 1997 International Conference on Multimedia Computing and Systems
Generation of interactive multi-level video summaries
MULTIMEDIA '03 Proceedings of the eleventh ACM international conference on Multimedia
Action movies segmentation and summarization based on tempo analysis
Proceedings of the 6th ACM SIGMM international workshop on Multimedia information retrieval
Tracking of moving objects based on graph edges similarity
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 3 (ICME '03) - Volume 03
Video summarization and scene detection by graph modeling
IEEE Transactions on Circuits and Systems for Video Technology
Video abstraction: A systematic review and classification
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Automatic classification of digestive organs in wireless capsule endoscopy videos
Proceedings of the 2007 ACM symposium on Applied computing
Clip based video summarization and ranking
CIVR '08 Proceedings of the 2008 international conference on Content-based image and video retrieval
Dynamic video summarization using two-level redundancy detection
Multimedia Tools and Applications
Key observation selection-based effective video synopsis for camera network
Machine Vision and Applications
Hi-index | 0.00 |
In this paper, we present scenario based dynamic video abstractions using graph matching. Our approach has two main components: multi-level scenario generations and dynamic video abstractions. Multi-level scenarios are generated by a graph-based video segmentation and a hierarchy of the segments. Dynamic video abstractions are accomplished by accessing the generated hierarchy level by level. The first step in the proposed approach is to segment a video into shots using Region Adjacency Graph (RAG). A RAG expresses spatial relationships among segmented regions of a frame. To measure the similarity between two consecutive RAGs, we propose a new similarity measure, called Graph Similarity Measure (GSM). Next, we construct a tree structure called scene tree based on the correlation between the detected shots. The correlation is computed by the GSM since it considers the relations between the detected shots properly. Multi-level scenarios which provide various levels of video abstractions are generated using the constructed scene tree. We provide two types of abstraction using multi-level scenarios: multi-level highlights and multi-length summarizations. Multi-level highlights are made by entire shots in each scenario level. To summarize a video in various lengths, we select key frames by considering temporal relationships among RAGs computed by the GSM. We have developed a system, called Automatic Video Analysis System (AVAS), by integrating the proposed techniques to show their effectiveness. The experimental results show that the proposed techniques are promising.