Multiple Cameras Using Real Time Object Tracking for Surveillance and Security System

Author(s):  
K Susheel Kumar ◽  
S Prasad ◽  
P K Saroj ◽  
R C Tripathi
2011 ◽  
Vol 403-408 ◽  
pp. 4968-4973
Author(s):  
Rajendra Kachhava ◽  
Vivek Srivastava ◽  
Rajkumar Jain ◽  
Ekta Chaturvedi

In this paper we propose multiple cameras using real time tracking for surveillance and security system. It is extensively used in the research field of computer vision applications, like that video surveillance, authentication systems, robotics, pre-stage of MPEG4 image compression and user inter faces by gestures. The key components of tracking for surveillance system are extracting the feature, background subtraction and identification of extracted object. Video surveillance, object detection and tracking have drawn a successful increased interest in recent years. A object tracking can be understood as the problem of finding the path (i.e. trajectory) and it can be defined as a procedure to identify the different positions of the object in each frame of a video. Based on the previous work on single detection using single stationary camera, we extend the concept to enable the tracking of multiple object detection under multiple camera and also maintain a security based system by multiple camera to track person in indoor environment, to identify by my proposal system which consist of multiple camera to monitor a person. Present study mainly aims to provide security and detect the moving object in real time video sequences and live video streaming. Based on a robust algorithm for human body detection and tracking in videos created with support of multiple cameras.


Author(s):  
In-Tae Jang ◽  
Dong-Woo Kim ◽  
Young-Jun Song ◽  
Hyeok-Bong Kwon ◽  
Jae-Hyeong Ahn

2011 ◽  
Vol 135-136 ◽  
pp. 70-75
Author(s):  
Ming Xin Jiang ◽  
Hong Yu Wang ◽  
Chao Lin

As a basic aspect of computer vision, reliable tracking of multiple objects is still an open and challenging issue for both theory studies and real applications. A novel multi-object tracking algorithm based on multiple cameras is proposed in this paper. We obtain the foreground likelihood maps in each view by modeling the background using the codebook algorithm. The view-to-view homographies are computed using several landmarks on the chosen plane. Then, we achieve the location information of multi-target at chest layer and realize the tracking task. The proposed algorithm does not require detecting the vanishing points of cameras, which reduces the complexity and improves the accuracy of the algorithm. The experimental results show that our method is robust to the occlusion and could satisfy the real-time tracking requirement.


Object tracking and face reorganization has received tremendous attention in the video processing community due to its various applications in video surveillance, traffic monitoring and so on. A single camera is not capable to scan 3d view of specified space. So, we use multiple cameras, placed in different sections of the area with overlapping region in field of view (FOV). Every camera will capture the video scene of itself FOV. The system is able to track human successfully by setting up correspondence between objects captured in multiple cameras. Thus, it saves the hectic job of manual tracking. There is a search window available for each object that gives the object’s trajectory. Tracking of object will be given by continuation of this process. For monitoring objects in areas like car parking, banks, hotels etc for security purpose, this system is best. Over the last couple of years, many algorithms and results have been presented for the problem of object tracking and recently the focus has been concentrated on real time person tracking with multiple cameras. Secondly, face detection is one of the best ways of identification. The main applications of automated face recognition are of biometric authentications and surveillances. Face recognition systems has became popular in biometric field as it is non intrusive and does not require the human interference. Up to that, there is no solution or technique that provides robust methods. This paper presents the detection of the face of the person, recognize and do tracking with use of multiple web cameras. Generally in daily camera security systems, cameras have been continuously remain on and large data storage is required in the system. In this real time object tracking system, Infrared sensors are used which indicates presence of person or object. Cameras will turn on only when object is detected by sensor after then the face recognition is carried out. It has capability of high speed processing and achieved low computational requirements. In similar areas, efficiency, accuracy, and speed of identification are the main tackled issues.


Author(s):  
Dimitrios Meimetis ◽  
Ioannis Daramouskas ◽  
Isidoros Perikos ◽  
Ioannis Hatzilygeroudis

Sign in / Sign up

Export Citation Format

Share Document