[KSCI] Korea Science Citation Index Service

http://dx.doi.org/10.3745/JIPS.02.0153

Multiple Properties-Based Moving Object Detection Algorithm

Zhou, Changjian (Dept. of Modern Educational Technology, Northeast Agricultural University)
Xing, Jinge (Dept. of Modern Educational Technology, Northeast Agricultural University)
Liu, Haibo (College of Computer Science and Technology, Harbin Engineering University)

Publication Information

Journal of Information Processing Systems / v.17, no.1, 2021 , pp. 124-135 More about this Journal

Abstract

Object detection is a fundamental yet challenging task in computer vision that plays an important role in object recognition, tracking, scene analysis and understanding. This paper aims to propose a multiproperty fusion algorithm for moving object detection. First, we build a scale-invariant feature transform (SIFT) vector field and analyze vectors in the SIFT vector field to divide vectors in the SIFT vector field into different classes. Second, the distance of each class is calculated by dispersion analysis. Next, the target and contour can be extracted, and then we segment the different images, reversal process and carry on morphological processing, the moving objects can be detected. The experimental results have good stability, accuracy and efficiency.

Keywords

Moving Object Detection; Multiple Properties; SIFT Vector Field;

Citations & Related Records

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