Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Adaptive Probabilistic Tracking Embedded in Smart Cameras for Distributed Surveillance in a 3D Model | Hindawi Publishing Corporation EURASIP Journal on Embedded Systems Volume 2007 Article ID 29858 17 pages doi 2007 29858 Research Article Adaptive Probabilistic Tracking Embedded in Smart Cameras for Distributed Surveillance in a 3D Model Sven Fleck Florian Busch and Wolfgang StraBer Wilhelm Schickard Institute for Computer Science Graphical-Interactive Systems WSI GRIS University of Tubingen Sand 14 72076 Tubingen Germany Received 27 April 2006 Revised 10 August 2006 Accepted 14 September 2006 Recommended by Moshe Ben-Ezra Tracking applications based on distributed and embedded sensor networks are emerging today both in the fields of surveillance and industrial vision. Traditional centralized approaches have several drawbacks due to limited communication bandwidth computational requirements and thus limited spatial camera resolution and frame rate. In this article we present network-enabled smart cameras for probabilistic tracking. They are capable of tracking objects adaptively in real time and offer a very bandwidthconservative approach as the whole computation is performed embedded in each smart camera and only the tracking results are transmitted which are on a higher level of abstraction. Based on this we present a distributed surveillance system. The smart cameras tracking results are embedded in an integrated 3D environment as live textures and can be viewed from arbitrary perspectives. Also a georeferenced live visualization embedded in Google Earth is presented. Copyright 2007 Sven Fleck et al. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. 1. INTRODUCTION In typical computer vision systems today cameras are seen only as simple sensors. The processing is performed after transmitting the complete raw sensor stream via a costly and often distance-limited connection to a centralized .
