A Wide Area Surveillance Video System by Combination of Omni-Directional and Network Controlled Cameras

2009 ◽  
Author(s):  
Yosuke Sato ◽  
Koji Hahsimoto ◽  
Yoshitaka Shibata
Keyword(s):  
Wide Area ◽  
Surveillance Video ◽  
Video System ◽  
Area Surveillance ◽  
Wide Area Surveillance

Efficient Key Frame Selection Approach for Object Detection in Wide Area Surveillance Applications

2019 ◽  
pp. 609-623
Author(s):  
Almabrok Essa ◽  
Paheding Sidike ◽  
Vijayan K. Asari
Keyword(s):  
Object Detection ◽  
Wide Area ◽  
Surveillance Video ◽  
Performance Impact ◽  
Frame Selection ◽  
Key Frame ◽  
Key Frame Selection ◽  
Area Surveillance ◽  
Surveillance Applications ◽  
Wide Area Surveillance

This paper presents an efficient preprocessing algorithm for object detection in wide area surveillance video analysis. The proposed key-frame selection method utilizes the pixel intensity differences among subsequent frames to automatically select only the frames that contain the desired contextual information and discard the rest of the insignificant frames. For improving effectiveness and efficiency, a batch updating based on a modular representation strategy is also incorporated. Experimental results show that the proposed key frame selection technique has a significant positive performance impact on wide area surveillance applications such as automatic object detection and recognition in aerial imagery.

Efficient Key Frame Selection Approach for Object Detection in Wide Area Surveillance Applications

2015 ◽  
Vol 3 (2) ◽  
pp. 20-34
Author(s):  
Almabrok Essa ◽  
Paheding Sidike ◽  
Vijayan K. Asari
Keyword(s):  
Object Detection ◽  
Wide Area ◽  
Surveillance Video ◽  
Pixel Intensity ◽  
Frame Selection ◽  
Key Frame ◽  
Key Frame Selection ◽  
Area Surveillance ◽  
Surveillance Applications ◽  
Wide Area Surveillance

This paper presents an efficient preprocessing algorithm for object detection in wide area surveillance video analysis. The proposed key-frame selection method utilizes the pixel intensity differences among subsequent frames to automatically select only the frames that contain the desired contextual information and discard the rest of the insignificant frames. For improving effectiveness and efficiency, a batch updating based on a modular representation strategy is also incorporated. Experimental results show that the proposed key frame selection technique has a significant positive performance impact on wide area surveillance applications such as automatic object detection and recognition in aerial imagery.

Survey and analysis of multimodal sensor planning and integration for wide area surveillance

2009 ◽  
Vol 41 (1) ◽  
pp. 1-36 ◽  
Author(s):  
Besma R. Abidi ◽  
Nash R. Aragam ◽  
Yi Yao ◽  
Mongi A. Abidi
Keyword(s):  
Wide Area ◽  
Sensor Planning ◽  
Area Surveillance ◽  
Wide Area Surveillance

Mine field detection algorithm utilizing data from an ultrawideband wide-area surveillance radar

1998 ◽  
Author(s):  
Lam H. Nguyen ◽  
Karl A. Kappra ◽  
David C. Wong ◽  
Ravinder Kapoor ◽  
Jeffrey Sichina
Keyword(s):  
Detection Algorithm ◽  
Wide Area ◽  
Mine Field ◽  
Field Detection ◽  
Area Surveillance ◽  
Wide Area Surveillance

scholarly journals A CNN-LSTM Network for Augmenting Target Detection in Real Maritime Wide Area Surveillance Radar Data

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 179281-179294
Author(s):  
Zachary Baird ◽  
Michael K. Mcdonald ◽  
Sreeraman Rajan ◽  
Simon J. Lee
Keyword(s):  
Target Detection ◽  
Radar Data ◽  
Wide Area ◽  
Area Surveillance ◽  
Lstm Network ◽  
Wide Area Surveillance
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