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This work addresses the problem of automatic tracking of pedestrians observed by a fixed camera in outdoor scenes. Tracking isolated pedestrians is not a difficult task. The challenge arises when the tracking system has to deal with temporary occlusions and groups of pedestrians. In both cases it is not possible to track each pedestrian during the whole(More)
This paper describes an algorithm for tracking groups of objects in video sequences. The main difficulties addressed in this work concern total occlusions of the objects to be tracked as well as group merging and splitting. A two layer solution is proposed to overcome these difficulties. The first layer produces a set of spatio temporal strokes based on low(More)
A video tracker should be able to track multiple objects in the presence of occlusions. This is a difficult task since there is not enough information during the occlusion time intervals. This paper proposes a tracking system which solves these difficulties, allowing a long term tracking of multiple interacting objects. First active regions are tracked(More)
It was recently proposed an object tracking method, which is able to deal with object occlusions and group tracking, using Bayesian networks. The Bayesian network (BN) tracker has shown promising results in difficult situations but its architecture is limited to a maximum of 2 parents/2 children per node, in order to avoid the combinatorial explosion and(More)
This paper presents and discusses the extended Via-Verde business model from the point of view of the underlying requirements for the virtual business processes. The extension of Via-Verde concept to other services beyond the motorway toll collection has increased the number of independent companies involved. The complex networked scenario resulted on a(More)
Real time monitoring of large infrastructures has human detection as a core task. Since the people anonymity is a hard constraint in these scenarios, video cameras can not be used. This paper presents a low cost solution for real time people detection in large crowded environments using multiple depth cameras. In order to detect people, binary classifiers(More)
It was recently proposed the use of Bayesian networks for object tracking. Bayesian networks allow to model the interaction among detected trajectories, in order to obtain a reliable object identification in the presence of occlu-sions. However, the architecture of the Bayesian network has been defined using simple heuristic rules which fail in many cases.(More)
Infrared images provide useful information to inspect the status of combustion processes. The flame geometry and intensity depend on the process variables and the characteristics of the combustion chamber. This paper describes methods to analyze infrared images of industrial flames and to characterize the flame geometry. A segmentation algorithm is proposed(More)
A tracking system based on Bayesian networks was recently proposed. This system deals with difficult situations (e.g., occlusions, group formation and splitting) trying to recover the object identity provided it appears isolated again. This requires an off line processing of the video sequence which prevents its use in real time applications such as video(More)