An Efficient Algorithm for Real Time Moving Object Detection using GMM and Optical Flow

Purpose The purpose of this paper is to meet the large demand for the new-generation intelligence monitoring systems that are used to detect targets within a dynamic background. Design/methodology/approach A dynamic target detection method based on the fusion of optical flow and neural network is proposed. Findings Simulation results verify the accuracy of the moving object detection based on optical flow and neural network fusion. The method eliminates the influence caused by the movement of the camera to detect the target and has the ability to extract a complete moving target. Practical implications It provides a powerful safeguard for target detection and targets the tracking application. Originality/value The proposed method represents the fusion of optical flow and neural network to detect the moving object, and it can be used in new-generation intelligent monitoring systems.

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FPGA-based real-time moving object detection for walking robots

2010 IEEE Safety Security and Rescue Robotics ◽

10.1109/ssrr.2010.5981554 ◽

2010 ◽

Cited By ~ 3

Author(s):

Andreas Laika ◽

Johny Paul ◽

Christopher Claus ◽

Walter Stechele ◽

Adam El Sayed Auf ◽

...

Keyword(s):

Object Detection ◽

Real Time ◽

Moving Object Detection ◽

Moving Object ◽

Walking Robots

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Real-time privacy-preserving moving object detection in the cloud

Proceedings of the 21st ACM international conference on Multimedia - MM '13 ◽

10.1145/2502081.2502157 ◽

2013 ◽

Cited By ~ 15

Author(s):

Kuan-Yu Chu ◽

Yin-Hsi Kuo ◽

Winston H. Hsu

Keyword(s):

Object Detection ◽

Real Time ◽

Privacy Preserving ◽

Moving Object Detection ◽

Moving Object

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Real-time moving object detection for video surveillance system in FPGA

Proceedings of the 2011 Conference on Design & Architectures for Signal & Image Processing (DASIP) ◽

10.1109/dasip.2011.6136881 ◽

2011 ◽

Cited By ~ 10

Author(s):

Tomasz Kryjak ◽

Mateusz Komorkiewicz ◽

Marek Gorgon

Keyword(s):

Object Detection ◽

Real Time ◽

Video Surveillance ◽

Surveillance System ◽

Moving Object Detection ◽

Moving Object ◽

Video Surveillance System

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Real-Time Moving Object Detection in High-Resolution Video Sensing

Sensors ◽

10.3390/s20123591 ◽

2020 ◽

Vol 20 (12) ◽

pp. 3591 ◽

Cited By ~ 1

Author(s):

Haidi Zhu ◽

Haoran Wei ◽

Baoqing Li ◽

Xiaobing Yuan ◽

Nasser Kehtarnavaz

Keyword(s):

High Resolution ◽

Object Detection ◽

Real Time ◽

Moving Object Detection ◽

Moving Object ◽

Computationally Efficient ◽

Real Time Processing ◽

Time Processing ◽

Video Frames ◽

High Resolution Images

This paper addresses real-time moving object detection with high accuracy in high-resolution video frames. A previously developed framework for moving object detection is modified to enable real-time processing of high-resolution images. First, a computationally efficient method is employed, which detects moving regions on a resized image while maintaining moving regions on the original image with mapping coordinates. Second, a light backbone deep neural network in place of a more complex one is utilized. Third, the focal loss function is employed to alleviate the imbalance between positive and negative samples. The results of the extensive experimentations conducted indicate that the modified framework developed in this paper achieves a processing rate of 21 frames per second with 86.15% accuracy on the dataset SimitMovingDataset, which contains high-resolution images of the size 1920 × 1080.

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