Dynamic Environmental Visual Image Identification and Monitoring Based on New Adaptive Segmentation.

It is an original study to integrate the computer vision and extreme activities for the academic research. A number of the extreme activities (sport and leisure) include a huge set of participants. These activities are dependent on weather conditions (sunshine, wind, wave, etc.) that have a direct or indirect effect. In this paper, a new adaptive image segmentation (NAIS) is proposed to search target data for the region of interest (ROI) area in globe histogram. After that, adaptive singular value decomposition (ASVD) is utilized to limit the variety of illumination for video images. HSV color model integrates computer vision techniques made to fit the dynamic environments for target detection. Besides, several tracking algorithms are applied to track the extreme activities. Experimental results show that the targets can be successfully detected and tracked in the sequential video images when performances of accurate tracking rate exceed 86.61% by Kalman filter (HSV) is better than other algorithms. [ABSTRACT FROM AUTHOR]