IJTEEE
International Journal of Technology Enhancements and Emerging Engineering Research (ISSN 2347-4289)
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IJTEEE >> Volume 2 - Issue 5, May 2014 Edition



International Journal of Technology Enhancements and Emerging Engineering Research  
International Journal of Technology Enhancements and Emerging Engineering Research

Website: http://www.ijteee.org

ISSN 2347-4289



"Object Tracking Using Multiple Cameras"

[Full Text]

 

AUTHOR(S)

Lalita Gavit, Reenal Sanghavi, Manasi Parab, Prof. Mohini P. Sardey

 

KEYWORDS

Keywords : FOV,SAD,MATLAB 7.12.0,FFMEG software.

 

ABSTRACT

ABSTRACT: A single camera is not capable of covering large areas. Hence, we use multiple cameras which are placed in different sections of the area to be covered. The cameras are placed with overlapping region between field of view (FOV) of different cameras. Each camera will capture the video of its FOV. The system is intelligent enough to track people successfully in multiple perspective imagery, by establishing correspondence between objects captured in multiple cameras. Thus, it saves the tedious job of manual tracking. The methodology used to track the object is the BLOCK METHOD ANALYSIS which works on the principle of prediction. A search window for each object in the frame is acquired which helps in giving us the trajectory of the object. Continuity of this process in each frame will give the track of the object. For tracking multiple objects, the system will give labeling to every object in the frame.There can be a possibility where one object will be hidden by another object in the FOV of any one of the cameras. This problem is referred to as occlusion. In such a situation, the tracking of the hidden object should not be stopped. Hence, occlusion needs to be detected and removed. Our system deals with this problem. This project will be useful in surveillance. Need of surveillance is to monitor people or objects in areas like car parking, hotels etc for security purpose. Use of such a system will be beneficial in places which require less labour and more efficiency. Thus, it is used for public benefit.

 

REFERENCES

[1] Hsiang-Kuo Tang( htang2@wisc.edu ), Tai-Hsuan Wu ( twu3@wisc.edu ), Ying-Tien Lin ( yingtien-lin@wisc.edu ) , “Real-time Object Image Tracking Based on Block-Matching Algorithm”

[2] Simone Calderara1, Andrea Prati2, Roberto Vezza-ni1, and Rita Cucchiara1,” Consistent Labeling for Multi-camera Object Tracking”

[3] Pier Luigi Mazzeo and Paolo Spagnolo Istituto sui Sistemi Intelligenti per l’automazione (CNR), Italy, “Object Tracking in Multiple Cameras with Disjoint Views”


[4] Santhosh Kumar Kadarla, “Object Tracking in Video Images based on Image segmentation and pattern matching.”

[5] “Digital Image Processing” by Rafael C. Gonzalez and Richard E. Woods.

[6] Bastian Leibe, Konrad Schindler, Nico Cornelis, and Luc Van Gool, Coupled Object Detection and Tracking from Static Cameras and Moving Vehicles