62,863 research outputs found

    Framework for real time behavior interpretation from traffic video

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    © 2005 IEEE.Video-based surveillance systems have a wide range of applications for traffic monitoring, as they provide more information as compared to other sensors. In this paper, we present a rule-based framework for behavior and activity detection in traffic videos obtained from stationary video cameras. Moving targets are segmented from the images and tracked in real time. These are classified into different categories using a novel Bayesian network approach, which makes use of image features and image-sequence- based tracking results for robust classification. Tracking and classification results are used in a programmed context to analyze behavior. For behavior recognition, two types of interactions have mainly been considered. One is interaction between two or more mobile targets in the field of view (FoV) of the camera. The other is interaction between targets and stationary objects in the environment. The framework is based on two types of a priori information: 1) the contextual information of the camera’s FoV, in terms of the different stationary objects in the scene and 2) sets of predefined behavior scenarios, which need to be analyzed in different contexts. The system can recognize behavior from videos and give a lexical output of the detected behavior. It also is capable of handling uncertainties that arise due to errors in visual signal processing. We demonstrate successful behavior recognition results for pedestrian– vehicle interaction and vehicle–checkpost interactions.Kumar, P.; Ranganath, S.; Huang Weimin; Sengupta, K

    Computer supported estimation of input data for transportation models

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    Control and management of transportation systems frequently rely on optimization or simulation methods based on a suitable model. Such a model uses optimization or simulation procedures and correct input data. The input data define transportation infrastructure and transportation flows. Data acquisition is a costly process and so an efficient approach is highly desirable. The infrastructure can be recognized from drawn maps using segmentation, thinning and vectorization. The accurate definition of network topology and nodes position is the crucial part of the process. Transportation flows can be analyzed as vehicle’s behavior based on video sequences of typical traffic situations. Resulting information consists of vehicle position, actual speed and acceleration along the road section. Data for individual vehicles are statistically processed and standard vehicle characteristics can be recommended for vehicle generator in simulation models

    A cross-layer approach to enhance QoS for multimedia applications over satellite

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    The need for on-demand QoS support for communications over satellite is of primary importance for distributed multimedia applications. This is particularly true for the return link which is often a bottleneck due to the large set of end-users accessing a very limited uplink resource. Facing this need, Demand Assignment Multiple Access (DAMA) is a classical technique that allows satellite operators to offer various types of services, while managing the resources of the satellite system efficiently. Tackling the quality degradation and delay accumulation issues that can result from the use of these techniques, this paper proposes an instantiation of the Application Layer Framing (ALF) approach, using a cross-layer interpreter(xQoS-Interpreter). The information provided by this interpreter is used to manage the resource provided to a terminal by the satellite system in order to improve the quality of multimedia presentations from the end users point of view. Several experiments are carried out for different loads on the return link. Their impact on QoS is measured through different application as well as network level metrics
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