In this paper we address the context of visual surveillance in outdoor environments involving the detection of moving objects in the observed scene. In particular, a reliable foreground segmentation, based on a background subtraction approach, is explored. We firstly address the problem arising when small movements of background objects, as trees blowing in the wind, generate false alarms. We p...

The quest for the best background subtraction technique is ongoing. Despite that a considerable e ort has been undertaken to develop exible and e cient methods, some elementary questions are still unanswered. One of them is the existence of an intrinsic upper bound to the performance. In fact, data are a ected by noise, and therefore it is illusory to believe that it is possible to achieve a pe...

In order to track and recognize the movements of multiple people using multiple cameras, each person needs to be segmented and identified in the image of each camera. We propose a method that tracks multiple people and identifies their body parts in multiple camera images. Estimation of the human positions and identification among the multiple cameras is mainly based on the silhouettes method c...

This paper presents a new background subtraction algorithm for mobile objects segmentation from a static background scene. Firstly, a case analysis of colour-motion segmentation problems is presented. Secondly, an architecture which fuses colour, intensity and edge cues is developed to cope the motion segmentation problems presented in the case analysis. Our approach first combines both colour ...

The video frame mainly consists of foreground and background objects. For effective detection and tracking of moving objects background subtraction is a very important part of surveillance applications for successful segmentation of objects from video sequences. In this paper we mainly survey these methods for autonomous detection and tracking of moving objects.

In this paper, we compare various image background subtraction algorithms with the ground truth of cars counted. We have given a sample of thousand images, which are the snap shots of current traffic as records at various intersections and highways. We have also counted an approximate number of cars that are visible in these images. In order to ascertain the accuracy of algorithms to be used fo...

09:30-09:50 Robust Background-Subtraction for Person Detection in Thermal Imagery, James W. Davis and Vinay Sharma, Ohio State U, Columbus, OH, USA 09:50-10:10 Motion Detection Based on Local Variation of Spatiotemporal Texture, Longin Jan Latecki, Roland Miezianko, Dragoljub Pokrajac, Temple University, Philadelphia, and Delaware State University, Dover, DE, USA 10:10-10:30 Pedestrian Detectio...

This paper proposes a method that tracks, and recognizes people in indoor scenes. Background subtraction and foreground silhouette analysis are used to detect people. The colour of each person’s clothes is used as a distinguishing feature for the purpose of tracking and recognizing people. Clothing colour is extracted using histograms on a luminance and perceptually uniform chrominance colour s...

An automatic object tracking and video summarization method for multi-camera systems with a large number of non-overlapping field-of-view cameras is explained. In this framework, 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. We...