Abstract: A real-time, semi-automatic method for discriminant track initialization in thermal imagery is very critical for tracking since it determines what to track for the tracker. Therefore, any insignificant or false information may result in redundant features or deceptive appearance that can cause premature track losses. To achieve long-term tracking, a real-time, semi-automatic track initialization methodology for IR images is proposed which takes a single image coordinate as input, then generates target bounding box for the most salient segment. The present invention is designed for real-time applications in which erroneous user input is unavoidable. Therefore, error compensation capability of present invention both introduces many practical advantageous together with performance boost. Low computational cost and requirement of only a point coordinate as input in the vicinity of the target make this approach preferable in real-time tracking applications.

Abstract: Target initialization can dramatically change the performance of the tracker, since the initial window determines for the tracker what to track. In order to achieve a better tracking performance; The present invention relates to a method of semi automatic target initialization based on visual saliency for a given point coordinate in the vicinity of target by the user. Performance boost of tracker is mainly based on two key features of target initialization algorithm: It is capable of compensating erroneous user input; also selecting the most distinctive, salient part of object as target, so better discrimination is achieved between the target and background. Experimental results show that tracking performance is boosted in scenarios, in which the tracking is initialized by the proposed algorithm. Very low computational cost and requirement of only a point coordinate as input in the neighborhood of the target make this approach preferable in real time tracking applications.

Abstract: A real-time, semi-automatic method for discriminant track initialization in thermal imagery is very critical for tracking since it determines what to track for the tracker. Therefore, any insignificant or false information may result in redundant features or deceptive appearance that can cause premature track losses. To achieve long-term tracking, a real-time, semi-automatic track initialization methodology for images is proposed which takes a single image coordinate as input, then generates target bounding box for the most salient segment. The present invention is designed for real-time applications in which erroneous user input is unavoidable. Therefore, error compensation capability of present invention both introduces many practical advantageous together with performance boost. Low computational cost and requirement of only a point coordinate as input in the vicinity of the target make this approach preferable in real-time tracking applications.

Abstract: Target initialization can dramatically change the performance of the tracker, since the initial window determines for the tracker what to track. In order to achieve a better tracking performance; The present invention relates to a method of semi automatic target initialization based on visual saliency for a given point coordinate in the vicinity of target by the user. Performance boost of tracker is mainly based on two key features of target initialization algorithm: It is capable of compensating erroneous user input; also selecting the most distinctive, salient part of object as target, so better discrimination is achieved between the target and background. Experimental results show that tracking performance is boosted in scenarios, in which the tracking is initialized by the proposed algorithm. Very low computational cost and requirement of only a point coordinate as input in the neighborhood of the target make this approach preferable in real time tracking applications.