Mean-shift background image modelling

M. Piccardi, T. Jan

Research output: Contribution to journalConference articlepeer-review

37 Citations (Scopus)


Background modelling is widely used in computer vision for the detection of foreground objects in a frame sequence. The more accurate the background model, the more correct is the detection of the foreground objects. In this paper, we present an approach to background modelling based on a mean-shift procedure. The mean shift vector convergence properties enable the system to achieve reliable background modelling. In addition, histogram-based computation and the new concept of local basins of attraction allow us to meet the stringent real-time requirements of video processing.

Original languageEnglish
Pages (from-to)3399-3402
Number of pages4
JournalProceedings - International Conference on Image Processing, ICIP
Publication statusPublished - 2004
Externally publishedYes
Event2004 International Conference on Image Processing, ICIP 2004 - , Singapore
Duration: 18 Oct 200421 Oct 2004


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