An Improved Kalman Filtering Algorithm for Moving Contact Detecting and Tracking

Based on the optical touch platform, this research firstly analyzes the principle of contact detecting and puts forward a method for single contact identifying and positioning. Secondly, facing the problems such as the disconnection often occurring in the process of user's fast lineation by the traditional contact positioning method, we have introduced the Kalman filtering algorithm for tracking the contact movement and have improved the model of the contact moving system to increase the dimensionality of the moving system state. The simulation test result on the OpenCV Platform has shown that the improved Kalman filtering algorithm can effectively enhance the tracking effect of the moving contact.

[1]  King Ngi Ngan,et al.  Video segmentation for content-based coding , 1999, IEEE Trans. Circuits Syst. Video Technol..

[2]  Zdenek Kalal,et al.  Tracking-Learning-Detection , 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[3]  Gilad Adiv,et al.  Determining Three-Dimensional Motion and Structure from Optical Flow Generated by Several Moving Objects , 1985, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[4]  Zhang Rui Methods for Estimation and Prediction of Maneuverable Target Based on Kalman Filtering , 2006 .

[5]  Shai Avidan,et al.  Support Vector Tracking , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[6]  Wenhui Li,et al.  Semantic image classification using statistical local spatial relations model , 2008, Multimedia Tools and Applications.

[7]  M. Meribout Video Segmentation for Content-based Coding , 2004 .

[8]  Larry S. Davis,et al.  W4: Real-Time Surveillance of People and Their Activities , 2000, IEEE Trans. Pattern Anal. Mach. Intell..