Multiple moving objects tracking for video surveillance systems

Tsai

Journal of the Chinese Institute of Engineers

et al. 2008

Current video surveillance systems are becoming digitalized and IP-based. With the development of the Internet, wireless and broadband networks, it is possible for a surveillance system client to ubiquitously access the surveillance system, i.e., to view the surveillance video and control the system remotely. One critical disadvantage of IPbased surveillance is the network reliability problem. That is, since the IP-based surveillance system is IP-based, all of the services provided by the IP-based surveillance system will not be accessible at all if network failure occurs. However, currently no related works address the network fault tolerance issue for IP-based surveillance systems. In this paper, possible network failure scenarios are investigated and determined. A network-fault-tolerant IP-based surveillance (NeTSurv) system is designed and implemented in the IPv6 network. In addition to the existing features of current video surveillance systems, a multihome-based approach is adopted to improve the network fault tolerance capability of the NeTSurv system. Two-level fault tolerance mechanisms are developed to solve the connectivity issue and the continuity issue of video playout for different link failure scenarios. With the devised mechanism, lost surveillance video data resulting from abrupt link failure can be recovered. Furthermore, a load balance mechanism is also devised for the NeTSurv system to distribute the load across multiple links. Using the load balance mechanism, congestion of a single link can be prevented when multiple clients request surveillance video through the Internet at the same time.

Section: Introductionmentioning

confidence: 97%

Netsurv: An IP‐based surveillance system with robust network fault tolerance and link load balance capabilities

Tsai

Journal of the Chinese Institute of Engineers

et al. 2008

2010 International Symposium on Intelligent Signal Processing and Communication Systems

“…The LL-band image produced by the original image size via two dimensions (row and column) calculation may cause high computing cost in the pre-processing. After dealing with the background subtraction, Alsaqre et al [7] used a local pre-process method to smooth the image with reducing noise and other small fluctuations. However, this approach is unable to 978-1-4244-7371-7/10/$26.00 ©201O IEEE reduce the post-processing computation.…”

Section: Introductionmentioning

confidence: 99%

Low resolution method using adaptive LMS scheme for moving objects detection and tracking

Hsia

Yeh

et al. 2010

This paper presents a new model for adaptive filter with the least-mean-square (LMS) scheme to train the mask operation on low resolution images. The adaptive filter theory with adaptive least-mean-square scheme (ALMSS) uses the training mask for moving object detection and tracking. However, the successful moving objects detection in a real surrounding environment is a difficult task due to noise issues such as fake motion or Gaussian noise. Many approaches have been developed in constrained environments to detect and track moving objects. On the other hand, the ALMSS approach can effectively reduce the noise with low computing cost in both fake motion and Gaussian noise environments. The experiments on real scenes indicate that the proposed ALMSS method is effective for moving object detection and tracking in real-time.

“…In all these applications extraction of moving objects from the video sequence is the key procedure. Since the camera is not in motion here, the inherent ambiguities of ego-motion is not considered and the scene structure can be rejected at the very beginning [1], [2].…”

Section: Introductionmentioning

confidence: 99%

Object Tracking System Using Approximate Median Filter, Kalman Filter and Dynamic Template Matching

Rao¹,

Satyanarayana²

2014

IJISA

In this work, we dealt with the tracking of single object in a sequence of frames either from a live camera or a previously saved video. A moving object is detected frame-by-frame with high accuracy and efficiency using Median approximation technique. As soon as the object has been detected, the same is tracked by kalman filter estimation technique along with a more accurate Template Matching algorithm. The templates are dynamically generated for this purpose. This guarantees any change in object pose which does not be hindered from tracking procedure. The system is capable of handling entry and exit of an object. Such a tracking scheme is cost effective and it can be used as an automated video conferencing system and also has application as a surveillance tool. Several trials of the tracking show that the approach is correct and extremely fast, and it's a more robust performance throughout the experiments.