Particle filter object tracking based on object feature and spatial information fusion

In the traditional particle filter tracking,color histogram is usually used as the features vectors,there are some limits because of the loss of space distribution.To overcome this problem,an efficient tracking algorithm based on object feature and spatial information fusion within particle filter framework is proposed.The dissimilarity between the referenced target and the target candidate is expressed by not only color,but also space distribution.At the same time for particle filter can be characterized by parallelism,OpenMP shared memory parallel computing is used for the acceleration of particle filter tracking.Experiments show that the algorithm can improve accuracy and speed for particle filter object tracking in the objectives and background of complex applications.