Spatiotemporal Motion Boundary Detection and Motion Boundary Velocity Estimation for Tracking Moving Objects With a Moving Camera: A Level Sets PDEs Approach With Concurrent Camera Motion Compensation

2004 ◽  
Vol 13 (11) ◽  
pp. 1473-1490 ◽  
Author(s):  
R. Feghali ◽  
A. Mitiche
Keyword(s):  
Motion Compensation ◽  
Level Sets ◽  
Moving Objects ◽  
Boundary Detection ◽  
Velocity Estimation ◽  
Camera Motion ◽  
Moving Camera ◽  
Boundary Velocity ◽  
Motion Boundary

MOVING OBJECT DETECTION FROM VIDEO CAPTURED BY MOVING SURVEILLANCE CAMERA

2021 ◽  
pp. 139-145
Author(s):  
Minh
Keyword(s):  
Object Detection ◽  
Template Matching ◽  
Moving Objects ◽  
Moving Object Detection ◽  
Object Motion ◽  
Moving Object ◽  
Camera Motion ◽  
Moving Camera ◽  
Image Differencing ◽  
Surveillance Camera

This paper presents an effective method for the detection of multiple moving objects from a video sequence captured by a moving surveillance camera. Moving object detection from a moving camera is difficult since camera motion and object motion are mixed. In the proposed method, we created a panoramic picture from a moving camera. After that, with each frame captured from this camera, we used the template matching method to found its place in the panoramic picture. Finally, using the image differencing method, we found out moving objects. Experimental results have shown that the proposed method had good performance with more than 80% of true detection rate on average.

Intelligent English classroom video clarity improvement based on motion compensation and grid flow

2020 ◽  
pp. 1-11
Author(s):  
Shufang Li ◽  
Wang Juan
Keyword(s):  
Motion Compensation ◽  
Noise Removal ◽  
Operating Efficiency ◽  
Camera Motion ◽  
Video Denoising ◽  
Actual Operating ◽  
Flow Motion ◽  
Pros And Cons ◽  
English Classroom ◽  
Teaching Video

For the English classroom teaching video denoising algorithm, it is not only necessary to consider whether the noise removal of the output video is thorough, but also to consider the actual operating efficiency and robustness of the algorithm. In the process of the thesis research, after reading a large number of internal and external documents on video denoising algorithms and analyzing the pros and cons of various denoising algorithms, this paper proposes a new video denoising algorithm, which uses the recently proposed grid flow motion model based on camera motion compensation to generate denoised video. Compared with the current advanced video denoising schemes, our method processes noisy frames faster and has good robustness. In addition, this article improves the algorithm framework so that the algorithm can not only deal with offline video denoising, but also deal with online video denoising.

scholarly journals Geometric Recognition of Moving Objects in Monocular Rotating Imagery Using Faster R-CNN

2020 ◽  
Vol 12 (12) ◽  
pp. 1908
Author(s):  
Tzu-Yi Chuang ◽  
Jen-Yu Han ◽  
Deng-Jie Jhan ◽  
Ming-Der Yang
Keyword(s):  
Object Recognition ◽  
Moving Objects ◽  
Low Cost ◽  
Three Dimensional ◽  
Real Life ◽  
Moving Object ◽  
Camera Motion ◽  
Ptz Camera ◽  
Real Life Data ◽  
Close Range

Moving object detection and tracking from image sequences has been extensively studied in a variety of fields. Nevertheless, observing geometric attributes and identifying the detected objects for further investigation of moving behavior has drawn less attention. The focus of this study is to determine moving trajectories, object heights, and object recognition using a monocular camera configuration. This paper presents a scheme to conduct moving object recognition with three-dimensional (3D) observation using faster region-based convolutional neural network (Faster R-CNN) with a stationary and rotating Pan Tilt Zoom (PTZ) camera and close-range photogrammetry. The camera motion effects are first eliminated to detect objects that contain actual movement, and a moving object recognition process is employed to recognize the object classes and to facilitate the estimation of their geometric attributes. Thus, this information can further contribute to the investigation of object moving behavior. To evaluate the effectiveness of the proposed scheme quantitatively, first, an experiment with indoor synthetic configuration is conducted, then, outdoor real-life data are used to verify the feasibility based on recall, precision, and F1 index. The experiments have shown promising results and have verified the effectiveness of the proposed method in both laboratory and real environments. The proposed approach calculates the height and speed estimates of the recognized moving objects, including pedestrians and vehicles, and shows promising results with acceptable errors and application potential through existing PTZ camera images at a very low cost.

Galvanometer control system design of aerial camera motion compensation

2015 ◽  
Author(s):  
Mingrui Qiao ◽  
Jianzhong Cao ◽  
Huawei Wang ◽  
Yunzeng Guo ◽  
Changchang Hu ◽  
...  
Keyword(s):  
Control System ◽  
System Design ◽  
Motion Compensation ◽  
Control System Design ◽  
Camera Motion

scholarly journals Fast generation of video holograms of three-dimensional moving objects using a motion compensation-based novel look-up table

2013 ◽  
Vol 21 (9) ◽  
pp. 11568 ◽  
Author(s):  
Seung-Cheol Kim ◽  
Xiao-Bin Dong ◽  
Min-Woo Kwon ◽  
Eun-Soo Kim
Keyword(s):  
Motion Compensation ◽  
Moving Objects ◽  
Three Dimensional ◽  
Look Up Table
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