Journal of Applied Mathematics / 2014 / Article / Alg 1

Research Article

Visual Tracking Using Max-Average Pooling and Weight-Selection Strategy

Algorithm 1

The proposed algorithm with max-average pooling.
Input: An image from the video sequences, the center point of the bounding box, the noise coefficient
, and the number of particles .
(1) Sample particles around the initial point of the bounding box, and the distribution of the particles
 is the normal distribution, which is implemented by the function randn.
(2) Initialize the dictionary using tracking results of the first ten frames.
(3) Compute the formula to obtain the sparse codes:
 Note that and , where is the size of the patch’ width by height.
(4) Pool the features by computing:
(5) Compute the error of reconstruction:
               
(6) Finally, obtain the particle which is corresponding to the minimum error.