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008 220601s2012 sz | s |||| 0|eng d
020 _a9783031018114
_9978-3-031-01811-4
024 7 _a10.1007/978-3-031-01811-4
_2doi
050 4 _aTA1501-1820
050 4 _aTA1634
072 7 _aUYT
_2bicssc
072 7 _aCOM016000
_2bisacsh
072 7 _aUYT
_2thema
082 0 4 _a006
_223
100 1 _aRoy-Chowdhury, Amit K.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_980163
245 1 0 _aCamera Networks
_h[electronic resource] :
_bThe Acquisition and Analysis of Videos over Wide Areas /
_cby Amit K Roy-Chowdhury, Bi Song.
250 _a1st ed. 2012.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2012.
300 _aXI, 119 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSynthesis Lectures on Computer Vision,
_x2153-1064
505 0 _aAn Introduction to Camera Networks -- Wide-Area Tracking -- Distributed Processing in Camera Networks -- Object and Activity Recognition -- Active Sensing -- Future Research Directions.
520 _aAs networks of video cameras are installed in many applications like security and surveillance, environmental monitoring, disaster response, and assisted living facilities, among others, image understanding in camera networks is becoming an important area of research and technology development. There are many challenges that need to be addressed in the process. Some of them are listed below: - Traditional computer vision challenges in tracking and recognition, robustness to pose, illumination, occlusion, clutter, recognition of objects, and activities; - Aggregating local information for wide area scene understanding, like obtaining stable, long-term tracks of objects; - Positioning of the cameras and dynamic control of pan-tilt-zoom (PTZ) cameras for optimal sensing; - Distributed processing and scene analysis algorithms; - Resource constraints imposed by different applications like security and surveillance, environmental monitoring, disaster response, assisted living facilities, etc. In this book, we focus on the basic research problems in camera networks, review the current state-of-the-art and present a detailed description of some of the recently developed methodologies. The major underlying theme in all the work presented is to take a network-centric view whereby the overall decisions are made at the network level. This is sometimes achieved by accumulating all the data at a central server, while at other times by exchanging decisions made by individual cameras based on their locally sensed data. Chapter One starts with an overview of the problems in camera networks and the major research directions. Some of the currently available experimental testbeds are also discussed here. One of the fundamental tasks in the analysis of dynamic scenes is to track objects. Since camera networks cover a large area, the systems need to be able to track over such wide areas where there could be both overlapping and non-overlapping fields of view of the cameras, as addressedin Chapter Two: Distributed processing is another challenge in camera networks and recent methods have shown how to do tracking, pose estimation and calibration in a distributed environment. Consensus algorithms that enable these tasks are described in Chapter Three. Chapter Four summarizes a few approaches on object and activity recognition in both distributed and centralized camera network environments. All these methods have focused primarily on the analysis side given that images are being obtained by the cameras. Efficient utilization of such networks often calls for active sensing, whereby the acquisition and analysis phases are closely linked. We discuss this issue in detail in Chapter Five and show how collaborative and opportunistic sensing in a camera network can be achieved. Finally, Chapter Six concludes the book by highlighting the major directions for future research. Table of Contents: An Introduction to Camera Networks / Wide-Area Tracking / Distributed Processing in Camera Networks / Object and Activity Recognition / Active Sensing / Future Research Directions.
650 0 _aImage processing
_xDigital techniques.
_94145
650 0 _aComputer vision.
_980164
650 0 _aPattern recognition systems.
_93953
650 1 4 _aComputer Imaging, Vision, Pattern Recognition and Graphics.
_931569
650 2 4 _aComputer Vision.
_980165
650 2 4 _aAutomated Pattern Recognition.
_931568
700 1 _aSong, Bi.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_980166
710 2 _aSpringerLink (Online service)
_980167
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031006838
776 0 8 _iPrinted edition:
_z9783031029394
830 0 _aSynthesis Lectures on Computer Vision,
_x2153-1064
_980168
856 4 0 _uhttps://doi.org/10.1007/978-3-031-01811-4
912 _aZDB-2-SXSC
942 _cEBK
999 _c84910
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