An algorithm based on particle filters is employed to track moving objects in video streams from fixed and non-fixed cameras. Particle weighting is based on color histograms computed in the iHLS color space. Particle computations are parallelized with CUDA framework. The algorithm was tested on various GPU devices: a desktop GPU card, a mobile chipset and two embedded GPU platforms. The processing speed depending on the number of particles and the size of a tracked object was measured. The aim of experiments was to assess the performance of the parallel algorithm and to test whether the currently available GPU devices are capable of real-time tracking of large moving objects in video streams from surveillance cameras.
Authors
Additional information
- Category
- Aktywność konferencyjna
- Type
- materiały konferencyjne indeksowane w Web of Science
- Language
- angielski
- Publication year
- 2016
