< Back to previous page

Project

Optimization of automatic video surveillance by multimodal video analysis

By merging the different kinds of data provided by visual, thermal and/or depth cameras, automatic video surveillance can achieve more accurate object detection. Since, besides the visual information, also thermal and depth information can be extracted, object identification can probably also be improved. New multimodal object detection and recognition techniques will be investigated to achieve these goals.

Date:1 Jan 2011 →  31 Oct 2015
Keywords:object detection, multimodal, video surveillance, object recognition
Disciplines:Information sciences, Scientific computing, Other information and computing sciences, Biological system engineering, Computer architecture and networks, Multimedia processing, Visual computing, Theoretical computer science, Signal processing, Programming languages, Distributed computing, Applied mathematics in specific fields, Information systems, Modelling