Research on Moving Object Detection Algorithm Based on Improved Three Frame Difference Method and Optical Flow

2015 ◽  
Author(s):  
Xiaowei Han ◽  
Yuan Gao ◽  
Zheng Lu ◽  
Zhimin Zhang ◽  
Dun Niu
Keyword(s):  
Object Detection ◽  
Optical Flow ◽  
Difference Method ◽  
Detection Algorithm ◽  
Moving Object Detection ◽  
Moving Object ◽  
Frame Difference

A Moving Object Detection Algorithm Based on ORB under Dynamic Scene

2014 ◽  
Vol 602-605 ◽  
pp. 1638-1641 ◽  
Author(s):  
Wen Hao Luo
Keyword(s):  
Object Detection ◽  
Difference Method ◽  
High Speed ◽  
Detection Algorithm ◽  
Moving Object Detection ◽  
Moving Object ◽  
Transformation Model ◽  
Dynamic Scene ◽  
Frame Difference ◽  
Inter Frame

In this thesis, a moving object detection algorithm under dynamic scene is proposed, which is based on ORB feature. Firstly, we extract feature points and match them by using ORB. We then obtain global motion compensation image by parameters of transformation matrix based on the RANSAC method. Finally, we use the inter-frame difference method to achieve the detection of moving targets. The high speed and accuracy of ORB feature point matching method, as well as the effectiveness of the RANSAC method for removing outliers ensure accurate calculation of parameters of affine transformation model. Combined with inter-frame difference method, foreground objects can be detected entirely. Experiment results show that the algorithm can accurately detect moving objects, and to some extent, it can solve the issue of real-time detection.

scholarly journals Underwater Moving Object Detection by Temporal Information

2019 ◽  
Vol 8 (3) ◽  
pp. 959-964
Keyword(s):  
Object Detection ◽  
Optical Flow ◽  
Prior Knowledge ◽  
Moving Object Detection ◽  
Moving Object ◽  
Video Frame ◽  
Morphological Operations ◽  
Statistical Parameters ◽  
Current Frame ◽  
Frame Difference

Underwater moving object detection is a critical task for many computer vision application such as object recognizing, locating and tracing. The low accuracy rate and absence of prior knowledge learning limits its application in various underwater application. This work proposes underwater moving object detection technique based on a temporal difference technique that extends basic frame difference method to multiple frames. The proposed technique does not require any prior knowledge such as background modeling nor interaction by user such as empirical thresholds tuning. Based on continuous symmetric difference of adjacent frames, we generate full resolution saliency map of current frame to highlight moving objects with higher saliency values. This process also aids in inhibiting saliency of background also. Individual frames are obtained from the video. Frame difference is calculated of two consecutive frames. Range filters are used to get edges of object and Morphological operations are used to suppress the noise present in the foreground. The proposed algorithm is tested for performance evaluation by performing various experiments under different conditions. The testing of proposed algorithm is done by visual and statistical parameters evaluated by simulation of different videos. Versatile Experiments have done to check performance of algorithm i.e. performance of proposed algorithm in low lighting conditions, performance of proposed method in case of shadow elimination, performance of proposed method in turbulent conditions, performance of proposed method in presence of multiple objects and performance of proposed method in case of false detections. In addition, comparison with most commonly techniques for object detection like GMM and Optical Flow is also done. The proposed technique provides effective results as contrast to GMM and Optical Flow

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