Adaptive Bayesian networks for video processing

Due to its static nature, the inference capability of Bayesian Networks (BNs) often deteriorates when the basis of input data varies, especially in video processing applications where the environment often changes constantly. This paper presents an adaptive BN where the network parameters are adjusted in accordance to input variations. An efficient re-training method is introduced for updating the parameters and the proposed network is applied to shadow removal in video sequence processing with quantitative results demonstrating the significance of adapting the network with environmental changes.

• Type: Conference
• Year: 2003
• Where: ICIP
• Authors: Benny P. L. Lo, Surapa Thiemjarus, Guang-Zhong Yang
• Keywords: Adaptive Bn, Efficient Re-training Method, ICIP 2003, Image Processing, Network Parameters, Video Processing Applications, Video Sequence Processing