Joint Exploitation of Features and Optical Flow for Real-Time Moving Object Detection on Drones

2019 ◽  
pp. 100-116
Author(s):  
Hazal Lezki ◽  
I. Ahu Ozturk ◽  
M. Akif Akpinar ◽  
M. Kerim Yucel ◽  
K. Berker Logoglu ◽  
...  
Keyword(s):  
Object Detection ◽  
Optical Flow ◽  
Real Time ◽  
Moving Object Detection ◽  
Moving Object

An implementation of real-time hardware for moving object detection and discrimination

2002 ◽  
Author(s):  
Young Ho Kim ◽  
Ihn Seok Suh ◽  
Byong Duk Nam ◽  
Jun Geun Jeon ◽  
Kyu Tae Park
Keyword(s):  
Object Detection ◽  
Real Time ◽  
Moving Object Detection ◽  
Moving Object

Moving object detection based on optical flow and neural network fusion

2016 ◽  
Vol 9 (4) ◽  
pp. 325-335 ◽  
Author(s):  
Haiqun Qin ◽  
Ziyang Zhen ◽  
Kun Ma
Keyword(s):  
Neural Network ◽  
Object Detection ◽  
Optical Flow ◽  
Target Detection ◽  
Moving Object Detection ◽  
Moving Object ◽  
Monitoring Systems ◽  
Dynamic Background ◽  
Content Type ◽  
New Generation

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.

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

2010 ◽  
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

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

Sensors ◽  
2020 ◽  
Vol 20 (12) ◽  
pp. 3591 ◽  
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.

Three-Pronged Compensation and Hysteresis Thresholding for Moving Object Detection in Real-Time Video Surveillance

2017 ◽  
Vol 64 (6) ◽  
pp. 4945-4955 ◽  
Author(s):  
Chia-Hung Yeh ◽  
Chih-Yang Lin ◽  
Kahlil Muchtar ◽  
Hsiang-Erh Lai ◽  
Ming-Ting Sun
Keyword(s):  
Object Detection ◽  
Real Time ◽  
Video Surveillance ◽  
Moving Object Detection ◽  
Moving Object ◽  
Hysteresis Thresholding
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