CONDENSATION—Conditional Density Propagation forVisual Tracking
International Journal of Computer Vision
Approximate Bayesian Multibody Tracking
IEEE Transactions on Pattern Analysis and Machine Intelligence
Using robust audio and video processing technologies to alleviate the elderly cognitive decline
Proceedings of the 1st international conference on PErvasive Technologies Related to Assistive Environments
Person tracking for ambient camera selection in complex sports environments
Proceedings of the 3rd international conference on Digital Interactive Media in Entertainment and Arts
A Person Tracking System for CHIL Meetings
Multimodal Technologies for Perception of Humans
An Appearance-Based Particle Filter for Visual Tracking in Smart Rooms
Multimodal Technologies for Perception of Humans
Optimised Meeting Recording and Annotation Using Real-Time Video Analysis
MLMI '08 Proceedings of the 5th international workshop on Machine Learning for Multimodal Interaction
Detection and localization of 3d audio-visual objects using unsupervised clustering
ICMI '08 Proceedings of the 10th international conference on Multimodal interfaces
AREA '08 Proceedings of the 1st ACM workshop on Analysis and retrieval of events/actions and workflows in video streams
An embedded audio-visual tracking and speech purification system on a dual-core processor platform
Microprocessors & Microsystems
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This paper focuses on the integration of acoustic and visual information for people tracking. The system presented relies on a probabilistic framework within which information from multiple sources is integrated at an intermediate stage. An advantage of the method proposed is that of using a generative approach which supports easy and robust integration of multi source information by means of sampled projection instead of triangulation. The system described has been developed in the EU funded CHIL Project research activities. Experimental results from the CLEAR evaluation workshop are reported.