Moving object extraction is a critical stage in a measurable 2D and 3D photogrammetric surveillance systems. In order to keep the frame rate of the live video, the chosen automatic method should be fast enough. Moreover, it is important to extract the moving objects precisely to be able to increase the accuracy of the measurements. Prior to the boundary extraction stage, the moving objects must...

An automatic object tracking and video summarization method for multicamera systems with a large number of non-overlapping field-of-view cameras is explained. In this system, video sequences are stored for each object as opposed to storing a sequence for each camera. Objectbased representation enables annotation of video segments, and extraction of content semantics for further analysis and sum...

We present a novel method to robustly and efficiently detect moving object, even under the complexity background, such as illumination changes, long shadows etc. This work is distinguished by three key contributions. The first is the integration of the Local Binary Pattern texture measure which extends the moving object detection work for light illumination changing. The second is the introduct...

Background modeling is important in video surveillance for extracting foreground regions from a complex environment. In this paper, we present a novel background modeling technique based on a special type of Markov Chain. The method is a substantial extension to the existing background subtraction techniques. First, a background pixel is statistically modeled by a linear regressive Gamma Markov...

In this paper, we present an approach for human fall detection, which has an important application in the field of safety and security. The proposed approach consists of two part: object detection and fall model. We use an adaptive background subtraction method to detect moving object and mark it with minimum-bounding box. Fall model uses a set of extracted features to analyze, detect and confi...

Surveillance in a maritime environment is indispensible in the fight against a wide range of criminal activities, including pirate attacks, unlicensed fishing trailers and human trafficking. Computer vision systems can be a useful aid in the law enforcement process, by for example tracking and identifying moving vessels on the ocean. However, the maritime domain poses many challenges for the de...

Identifying objects of interest from a video sequence is a fundamental and essential part in many vision systems. A common method is to perform background subtraction. For automated surveillance systems, real-time background subtraction is especially important to ensure the performance of the systems. In this paper, we review various background subtraction algorithms in a binary hypothesis test...

This tutorial will cover problems related to detection and tracking from surveillance video. For detection, I will cover background subtraction for fixed and pan/tilt/zoom cameras, shape-based detection using machine learning techniques, and the use of periodic motion models to discriminate people from other moving objects in video. For tracking, I will discuss discus basic representation and c...

This paper reviews papers on tracking people in a video surveillance system, and it presents a new system designed for being able to cope with shadows in a real-time application for counting people which is one of the remaining main problems in adaptive background subtraction in such video surveillance systems. 1 Reveal Ltd., Level 1, Tudor Mall, 333 Remuera Rd, Auckland, New Zealand 2 CITR, De...

A new method of background subtraction is presented which uses the concept of a signal estimator to construct a confidence level which is always conservative and which is never better than e. The new method yields stronger exclusions than the Bayesian method with a flat prior distribution. (Submitted to Nuclear Instruments and Methods A.) Corresponding address: CERN/EP Division, 1211 Geneva 23,...