VIDEX: an integrated generic video indexing approach
MULTIMEDIA '00 Proceedings of the eighth ACM international conference on Multimedia
The SMOOTH video DB - demonstration of an integrated generic indexing approach
MULTIMEDIA '00 Proceedings of the eighth ACM international conference on Multimedia
Unsupervised Segmentation of Color-Texture Regions in Images and Video
IEEE Transactions on Pattern Analysis and Machine Intelligence
Content-based visual information retrieval
Distributed multimedia databases
Model-Based Video Classification toward Hierarchical Representation, Indexing and Access
Multimedia Tools and Applications
A Probabilistic Framework for Spatio-Temporal Video Representation & Indexing
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
Video Object Hyper-Links for Streaming Applications
VISUAL '02 Proceedings of the 5th International Conference on Recent Advances in Visual Information Systems
A Motion Activity Descriptor and Its Extraction in Compressed Domain
PCM '01 Proceedings of the Second IEEE Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
A hierarchical access control model for video database systems
ACM Transactions on Information Systems (TOIS)
Accessing Video Contents through Key Objects over IP
Multimedia Tools and Applications
Probabilistic Space-Time Video Modeling via Piecewise GMM
IEEE Transactions on Pattern Analysis and Machine Intelligence
ETP '03 Proceedings of the 2003 ACM SIGMM workshop on Experiential telepresence
A motion-flow-based fast video retrieval system
Proceedings of the 7th ACM SIGMM international workshop on Multimedia information retrieval
Context-Based Segmentation of Image Sequences
IEEE Transactions on Pattern Analysis and Machine Intelligence
Visual information retrieval: minerva video benchmark
SPPRA'06 Proceedings of the 24th IASTED international conference on Signal processing, pattern recognition, and applications
Clustering in video data: Dealing with heterogeneous semantics of features
Pattern Recognition
Analysis of vector space model and spatiotemporal segmentation for video indexing and retrieval
Proceedings of the 6th ACM international conference on Image and video retrieval
EURASIP Journal on Applied Signal Processing
Search the audio, browse the video: a generic paradigm for video collections
EURASIP Journal on Applied Signal Processing
Content based video matching using spatiotemporal volumes
Computer Vision and Image Understanding
A Novel Approach to Spatio-Temporal Video Analysis and Retrieval
MIRAGE '09 Proceedings of the 4th International Conference on Computer Vision/Computer Graphics CollaborationTechniques
Trajectory tree as an object-oriented hierarchical representation for video
IEEE Transactions on Circuits and Systems for Video Technology
Fast min-hashing indexing and robust spatio-temporal matching for detecting video copies
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Content-based retrieval for human motion data
Journal of Visual Communication and Image Representation
Spatio-temporal descriptor using 3D curvature scale space
PReMI'07 Proceedings of the 2nd international conference on Pattern recognition and machine intelligence
Approximation algorithm for the kinetic robust K-center problem
Computational Geometry: Theory and Applications
An automated video annotation system
ICAPR'05 Proceedings of the Third international conference on Pattern Recognition and Image Analysis - Volume Part II
MPEG-4 video retrieval using video-objects and edge potential functions
PCM'04 Proceedings of the 5th Pacific Rim conference on Advances in Multimedia Information Processing - Volume Part III
Extracting representative motion flows for effective video retrieval
Multimedia Tools and Applications
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We present a prototype video analysis and retrieval system, called NeTra-V, that is being developed to build an object-based video representation for functionalities such as search and retrieval of video objects. A region-based content description scheme using low-level visual descriptors is proposed. In order to obtain regions for local feature extraction, a new spatio-temporal segmentation and region-tracking scheme is employed. The segmentation algorithm uses all three visual features: color, texture, and motion in the video data. A group processing scheme similar to the one in the MPEG-2 standard is used to ensure the robustness of the segmentation. The proposed approach can handle complex scenes with large motion. After segmentation, regions are tracked through the video sequence using extracted local features. The results of tracking are sequences of coherent regions, called “subobjects”. Subobjects are the fundamental elements in our low-level content description scheme, which can be used to obtain meaningful physical objects in a high-level content description scheme. Experimental results illustrating segmentation and retrieval are provided