Research on Motion Attention Fusion Model-Based Video Target Detection and Extraction of Global Motion Scene

Long Liu, Boyang Fan, Jing Zhao

The Faculty of Automation and Information Engineering, Xi’an University of Technology, Xi’an, China..

DOI: 10.4236/jsip.2013.43B006                

Abstract

For target detection algorithm under global motion scene, this paper suggests a target detection algorithm based on motion attention fusion model. Firstly, the motion vector field is pre-processed by accumulation and median filter; Then, according to the temporal and spatial character of motion vector, the attention fusion model is defined, which is used to detect moving target; Lastly, the edge of video moving target is made exactly by morphologic operation and edge tracking algorithm. The experimental results of different global motion video sequences show the proposed algorithm has a better veracity and speedup than other algorithm.

Keywords

Target Detection; Attention Model; Global Scene

Conflicts of Interest

The authors declare no conflicts of interest.

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