Maximally Stable Extremal Regions Improved Tracking Algorithm Based on Depth Image

被引：0

作者：

Wang, Haikuan ^{[1
]}

Xie, Dong ^{[1
]}

Sun, Haoxiang ^{[1
]}

Zhou, Wenju ^{[1
]}

机构：

[1] Shanghai Univ, Sch Mech Engn & Automat, 99 Shangda Rd, Shanghai 200444, Peoples R China

来源：

INTELLIGENT COMPUTING AND INTERNET OF THINGS, PT II | 2018年 / 924卷

关键词：

Depth image; MSER algorithm; Target tracking; Camshift algorithm;

D O I：

10.1007/978-981-13-2384-3_51

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In order to solve the problem that traditional Camshift algorithm can easily fail to track overlapping targets and multiple similar depth targets, a new improved maximally stable extremal regions (MSER) algorithm is presented in this paper. Firstly, the suspected target contour is extracted and similarity analysis is performed. Secondly, the improved MSER algorithm is used to confirm the target contour and update the similarity library. Finally, combined with the physical properties unique to the depth image and based on the Kalman filter, it is possible to predict the tracking target's moving position. The experimental results show that the real-time performance and recognition rate are improved, and robustness to the situation of target overlap and occlusion is better with the improved MSER algorithm.

引用

页码：546 / 554

页数：9

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