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—Background subtraction methods are widely exploited for moving object detection in videos in many applications, such as traffic monitoring, human motion capture, and video surveillance. How to correctly and efficiently model and update the background model and how to deal with shadows are two of the most distinguishing and challenging aspects of such(More)
There is a large variety of trackers, which have been proposed in the literature during the last two decades with some mixed success. Object tracking in realistic scenarios is a difficult problem, therefore, it remains a most active area of research in computer vision. A good tracker should perform well in a large number of videos involving illumination(More)
— Video-surveillance and traffic analysis systems can be heavily improved using vision-based techniques able to extract, manage and track objects in the scene. However , problems arise due to shadows. In particular, moving shadows can affect the correct localization, measurements and detection of moving objects. This work aims to present a technique for(More)
1 Abstract—Moving shadows need careful consideration in the development of robust dynamic scene analysis systems. Moving shadow detection is critical for accurate object detection in video streams, since shadow points are often mis-classified as object points causing errors in segmentation and tracking. Many algorithms have been proposed in the literature(More)
To help accelerate progress in multi-target, multi-camera tracking systems, we present (i) a new pair of precision-recall measures of performance that treats errors of all types uniformly and emphasizes correct identification over sources of error; (ii) the largest fully-annotated and calibrated data set to date with more than 2 million frames of 1080p,(More)
Many approaches to moving object detection for traffic monitoring and video surveillance proposed in the literature are based on background suppression methods. How to correctly and efficiently update the background model and how to deal with shadows are two of the more distinguishing and challenging features of such approaches. This work presents a(More)
In this paper, we define a new paradigm for eight-connection labeling, which employes a general approach to improve neighborhood exploration and minimizes the number of memory accesses. First, we exploit and extend the decision table formalism introducing or-decision tables, in which multiple alternative actions are managed. An automatic procedure to(More)
The integration of video technology and sensor networks constitutes the fundamental infrastructure for new generations of <i>multimedia surveillance systems</i>, where many different media streams (audio, video, images, textual data, sensor signals) will concur to provide an automatic analysis of the controlled environment and a real-time interpretation of(More)
Robustness to changes in illumination conditions as well as viewing perspectives is an important requirement for many computer vision applications. One of the key factors in enhancing the robustness of dynamic scene analysis is that of accurate and reliable means for shadow detection. Shadow detection is critical for correct object detection in image(More)
In Constraint Satisfaction Problems (CSPs) values belonging to variable domains should be completely known before the constraint propagation process starts. In many applications, however, the acquisition of domain values is a computational expensive process or some domain values could not be available at the beginning of the computation. For this purpose,(More)