Energy Efficient Camera Solution for Video Surveillance

Video surveillance is growing rapidly, new problems and issues are also coming into view which needs serious and urgent attention. Video surveillance system requires a beneficial energy efficient camera solution. In this paper, a single overhead camera solution is introduced which overcomes the problems ex-isting in various frontal and overhead based surveillance systems. This will increases the efficiency and accuracy of surveillance system i.e. frontal and overhead. In this paper, two energy efficient overhead camera models are presented. The first model consists of a single overhead camera with a wide angle lens which covers a wide field of view addresses problems present in the traditional surveillance system. The second model, presents a single smart centralized overhead camera which controls various frontal based cameras. Several factors associated with camera models such as field of view, focal length and distortion are also discussed. Impact of the surveillance cameras are finally discussed which shows that a single energy efficient overhead camera surveillance system can solves many problems present in traditional surveillance system like power consumption, storage, time, human resource and installation cost and small coverage area.

[1]  Shu-Yin Chiang,et al.  Cooperative dual camera surveillance system for real-time object searching and close-up viewing , 2016, 2016 2nd International Conference on Intelligent Green Building and Smart Grid (IGBSG).

[2]  Bill Triggs,et al.  Histograms of oriented gradients for human detection , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[3]  Mohan S. Kankanhalli,et al.  Multi-Camera Coordination and Control in Surveillance Systems , 2015, ACM Trans. Multim. Comput. Commun. Appl..

[4]  Sapana K. Mishra,et al.  A Survey on Human Motion Detection and Surveillance , 2015 .

[5]  Ting-En Tseng,et al.  Real-time people detection and tracking for indoor surveillance using multiple top-view depth cameras , 2014, 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[6]  Jinwen Ma,et al.  Combination features and models for human detection , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[7]  Thomas S. Huang,et al.  Vision-based overhead view person recognition , 2000, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000.

[8]  Li-Chen Fu,et al.  The manhunt network: People tracking in hybrid-overlapping under the vertical top-view depth camera networks , 2016, 2016 International Conference on Advanced Robotics and Intelligent Systems (ARIS).

[9]  Cordelia Schmid,et al.  Human Detection Based on a Probabilistic Assembly of Robust Part Detectors , 2004, ECCV.

[10]  Samir Bouaziz,et al.  3D-sensing Distributed Embedded System for People Tracking and Counting , 2015, 2015 International Conference on Computational Science and Computational Intelligence (CSCI).

[11]  Kazutaka Shimada,et al.  A Person Identification Method Using a Top-View Head Image from an Overhead Camera , 2012, J. Adv. Comput. Intell. Intell. Informatics.

[12]  Marco A. Wehrmeister,et al.  Using Deep Learning and Low-Cost RGB and Thermal Cameras to Detect Pedestrians in Aerial Images Captured by Multirotor UAV , 2018, Sensors.

[13]  Imran Ahmed,et al.  A robust algorithm for detecting people in overhead views , 2017, Cluster Computing.

[14]  Sridha Sridharan,et al.  A Database for Person Re-Identification in Multi-Camera Surveillance Networks , 2012, 2012 International Conference on Digital Image Computing Techniques and Applications (DICTA).

[15]  Ki-Hong Kim,et al.  Human detection in top-view depth image , 2016 .

[16]  Mario Vento,et al.  An efficient and effective method for people detection from top-view depth cameras , 2017, 2017 14th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS).

[17]  Mario Vento,et al.  A versatile and effective method for counting people on either RGB or depth overhead cameras , 2015, 2015 IEEE International Conference on Multimedia & Expo Workshops (ICMEW).

[18]  John N. Carter,et al.  A robust person detector for overhead views , 2012, Proceedings of the 21st International Conference on Pattern Recognition (ICPR2012).

[19]  Ali Yeon Md Shakaff,et al.  A robust multimedia surveillance system for people counting , 2017, Multimedia Tools and Applications.

[20]  José Luis Lázaro,et al.  Directional People Counter Based on Head Tracking , 2013, IEEE Transactions on Industrial Electronics.

[21]  Bernt Schiele,et al.  Multi-person Tracking by Multicut and Deep Matching , 2016, ECCV Workshops.

[22]  Rogelio Lozano,et al.  Human detection in uncluttered environments: From ground to UAV view , 2014, 2014 13th International Conference on Control Automation Robotics & Vision (ICARCV).

[23]  Yoong Choon Chang,et al.  A simple vision-based fall detection technique for indoor video surveillance , 2015, Signal Image Video Process..