Optimization of automatic video surveillance by multimodal video analysis

01 January 2011 → 31 October 2015
Ghent University funding
Research disciplines
  • Natural sciences
    • Applied mathematics in specific fields
    • Computer architecture and networks
    • Distributed computing
    • Information sciences
    • Information systems
    • Programming languages
    • Scientific computing
    • Theoretical computer science
    • Visual computing
    • Other information and computing sciences
  • Engineering and technology
    • Modelling
    • Multimedia processing
    • Biological system engineering
    • Signal processing
object detection multimodal video surveillance object recognition
Project description

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.