A moving target detection algorithm based on GMM and improved Otsu method

2014 ◽  
Author(s):  
Zhe Zhao ◽  
Yingqing Huang ◽  
Xiaoyu Jiang ◽  
Xingpeng Yan
Keyword(s):  
Target Detection ◽  
Detection Algorithm ◽  
Moving Target ◽  
Moving Target Detection ◽  
Otsu Method

A Calculating Method for Adaptive Human Shadows Moving Target Detection Algorithm

2014 ◽  
Vol 667 ◽  
pp. 255-259
Author(s):  
Fei Tang ◽  
Jin Xiong Zhang ◽  
Te Cai ◽  
Sen Guo ◽  
Re Qiang
Keyword(s):  
Target Detection ◽  
Detection Algorithm ◽  
Good Effect ◽  
Moving Target ◽  
Moving Target Detection ◽  
Calculating Method ◽  
Video Images ◽  
Distribution Histogram ◽  
Otsu Method ◽  
High Detection

Based on the analysis of video images HSV differential and differential histogram chart and its pixel distribution histogram goals and shadow, this paper raises an Otsu method based on weighted shadow detection algorithm. The experiment shows this calculating method is featured by high detection precision, good effect, adaptability, easy realization of the project.

Moving Target Detection Based on Principle of Connectivity and Texture Gradient

2012 ◽  
Vol 605-607 ◽  
pp. 2117-2120
Author(s):  
Min Huang ◽  
Yang Zhang ◽  
Gang Chen ◽  
Guo Feng Yang
Keyword(s):  
Target Detection ◽  
Detection Algorithm ◽  
Experimental Results ◽  
Texture Gradient ◽  
Moving Target ◽  
Moving Target Detection ◽  
Gradient Information ◽  
Target Segmentation ◽  
Target Profile

In target detection, “hole” phenomenon is present in the detection result, and the shadow is difficult to remove. To solve these problems, we propose a target detection algorithm based on principle of connectivity and texture gradient. Firstly, we use the connectivity principle to find the largest target prospects connection area to get a complete target contour, secondly we use target texture gradient information to further remove the shadow of the target. At last, the experimental results show that the algorithm can obtain a clear target profile and improve the accuracy of the moving target segmentation.

Dim moving target detection algorithm based on spatio-temporal classification sparse representation

2014 ◽  
Vol 67 ◽  
pp. 273-282 ◽  
Author(s):  
Zhengzhou Li ◽  
Zhen Dai ◽  
Hongxia Fu ◽  
Qian Hou ◽  
Zhen Wang ◽  
...  
Keyword(s):  
Sparse Representation ◽  
Target Detection ◽  
Detection Algorithm ◽  
Moving Target ◽  
Moving Target Detection ◽  
Spatio Temporal

scholarly journals Recognition of Student Classroom Behaviors Based on Moving Target Detection

2021 ◽  
Vol 38 (1) ◽  
pp. 215-220
Author(s):  
Bin Wu ◽  
Chunmei Wang ◽  
Wei Huang ◽  
Da Huang ◽  
Hang Peng
Keyword(s):  
Target Detection ◽  
Classroom Environment ◽  
Skin Color ◽  
Student Behavior ◽  
Region Of Interest ◽  
Detection Algorithm ◽  
Recognition Algorithm ◽  
Moving Target ◽  
Classroom Behaviors ◽  
Moving Target Detection

Classroom teaching, as the basic form of teaching, provides students with an important channel to acquire information and skills. The academic performance of students can be evaluated and predicted objectively based on the data on their classroom behaviors. Considering the complexity of classroom environment, this paper firstly envisages a moving target detection algorithm for student behavior recognition in class. Based on region of interest (ROI) and face tracking, the authors proposed two algorithms to recognize the standing behavior of students in class. Moreover, a recognition algorithm was developed for hand raising in class based on skin color detection. Through experiments, the proposed algorithms were proved as effective in recognition of student classroom behaviors.

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