The theory and practice of Bayesian image labeling
International Journal of Computer Vision
Machine Learning
VideoQ: an automated content based video search system using visual cues
MULTIMEDIA '97 Proceedings of the fifth ACM international conference on Multimedia
Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
An Integrated Bayesian Approach to Layer Extraction from Image Sequences
IEEE Transactions on Pattern Analysis and Machine Intelligence
Video Segmentation by MAP Labeling of Watershed Segments
IEEE Transactions on Pattern Analysis and Machine Intelligence
Interactive tools for constructing and browsing structures for movie films
MULTIMEDIA '00 Proceedings of the eighth ACM international conference on Multimedia
Markov random field modeling in image analysis
Markov random field modeling in image analysis
Media Computing: Computational Media Aesthetics
Media Computing: Computational Media Aesthetics
The Application of Video Semantics and Theme Representation in Automated Video Editing
Multimedia Tools and Applications
Hierarchical video indexing based on changes of camera and object motions
Proceedings of the 2003 ACM symposium on Applied computing
Layered Motion Segmentation and Depth Ordering by Tracking Edges
IEEE Transactions on Pattern Analysis and Machine Intelligence
Discovering Semantics from Visualizations of Film Takes
MMM '04 Proceedings of the 10th International Multimedia Modelling Conference
Multimodal Video Indexing: A Review of the State-of-the-art
Multimedia Tools and Applications
Sports video categorizing method using camera motion parameters
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 1
Using camera motion to identify types of American football plays
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 1
Joint optical flow estimation, segmentation, and 3D interpretation with level sets
Computer Vision and Image Understanding
A generic framework of user attention model and its application in video summarization
IEEE Transactions on Multimedia
Models for motion-based video indexing and retrieval
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Multiple motion segmentation with level sets
IEEE Transactions on Image Processing
Spatio-temporal indexing of vector quantized video sequences
IEEE Transactions on Circuits and Systems for Video Technology
Automatic segmentation of moving objects in video sequences: a region labeling approach
IEEE Transactions on Circuits and Systems for Video Technology
IEEE Transactions on Circuits and Systems for Video Technology
Video object segmentation using Bayes-based temporal tracking and trajectory-based region merging
IEEE Transactions on Circuits and Systems for Video Technology
Automatic moving object extraction for content-based applications
IEEE Transactions on Circuits and Systems for Video Technology
Fast coarse-to-fine video retrieval using shot-level spatio-temporal statistics
IEEE Transactions on Circuits and Systems for Video Technology
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The immense indexing potential of motion cues has hitherto been realized only in domains with more apparent structure (e.g., sport videos). To address the lack of theoretical attention and to realize the potential of motion-based indexing in the subtler film domain, we propose a systematic approach to build taxonomy for film directing semantics. These motionrelated semantics are grounded upon cinematography and are thus more appealing to users. In order to automate the classification of these semantics, we have developed a novel markov random field based motion segmentation algorithm with an integral foreground/background identification capability based on edge occlusion reasoning. This algorithm is sufficiently robust and fast for film domain conditions, and allows us to formulate salient and novel motion descriptors capable of mapping to the proposed directing semantics. We demonstrate the validity of the framework and effectiveness of the motion-based descriptors by classifying shots from Hollywood domain movies according to the proposed taxonomy with satisfactory results.