Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
W4: Real-Time Surveillance of People and Their Activities
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Bayesian Computer Vision System for Modeling Human Interactions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recognition of Visual Activities and Interactions by Stochastic Parsing
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiobject Behavior Recognition by Event Driven Selective Attention Method
IEEE Transactions on Pattern Analysis and Machine Intelligence
Example-Based Object Detection in Images by Components
IEEE Transactions on Pattern Analysis and Machine Intelligence
Video Annotation for Content-based Retrieval using Human Behavior Analysis and Domain Knowledge
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
Computer and Intrusion Forensics
Computer and Intrusion Forensics
Strategies for Positive and Negative Relevance Feedback in Image Retrieval
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 1
Image Mining and Retrieval Using Hierarchical Support Vector Machines
MMM '05 Proceedings of the 11th International Multimedia Modelling Conference
EyesWeb - Toward Gesture and Affect Recognition in Dance/Music Interactive Systems
ICMCS '99 Proceedings of the IEEE International Conference on Multimedia Computing and Systems - Volume 2
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Increasing amount of illicit image data transmitted via the internet has triggered the need to develop effective image mining systems for digital forensics purposes. This paper discusses the requirements of digital image forensics which underpin the design of our forensic image mining system. This system can be trained by a hierarchical Support Vector Machine (SVM) to detect objects and scenes which are made up of components under spatial or non-spatial constraints. Forensic investigators can communicate with the system via a grammar which allows object description for training, searching, querying and relevance feedback. In addition, we propose to use a Bayesian networks approach to deal with information uncertainties which are inherent in forensic work. These inference networks will be constructed to model probability interactions between beliefs, adapt to different users' retrieval patterns, and mimic human judgement of semantic content of image patches. An analysis of the performance of the first prototype of the system is also provided.