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[null,"1.","Record Nr.",null,"UNINA9910437600903321"]
[null,null,"Titolo",null,"Consumer Depth Cameras for Computer Vision [[electronic resource] ] : Research Topics and Applications / / edited by Andrea Fossati, Juergen Gall, Helmut Grabner, Xiaofeng Ren, Kurt Konolige"]
[null,null,"Pubbl/distr/stampa",null,"London : , : Springer London : , : Imprint : Springer, , 2013"]
[null,null,"ISBN",null,"1-283-90966-9"]
[{"$nulls":4},"1-4471-4640-9"]
[null,null,"Edizione",null,"[1st ed. 2013.]"]
[null,null,"Descrizione fisica",null,"1 online resource (219 p.)"]
[null,null,"Collana",null,"Advances in Computer Vision and Pattern Recognition, , 2191-6586"]
[null,null,"Disciplina",null,"006.3"]
[{"$nulls":4},"006.3/7"]
[{"$nulls":4},"006.37"]
[null,null,"Soggetti",null,"Optical data processing"]
[{"$nulls":4},"Pattern recognition"]
[{"$nulls":4},"Computer graphics"]
[{"$nulls":4},"Image Processing and Computer Vision"]
[{"$nulls":4},"Pattern Recognition"]
[{"$nulls":4},"Computer Graphics"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[{"$nulls":3},"Livello bibliografico","Monografia"]
[{"$nulls":3},"Note generali","Description based upon print version of record."]
[{"$nulls":3},"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,"Nota di contenuto",null,"Part I: 3D Registration and Reconstruction -- 3D with Kinect -- Real-Time RGB-D Mapping and 3-D Modeling on the GPU using the Random Ball Cover -- A Brute Force Approach to Depth Camera Odometry -- Part II: Human Body Analysis -- Key Developments in Human Pose Estimation for Kinect -- A Data-Driven Approach for Real-Time Full Body Pose Reconstruction from a Depth Camera -- Home 3D Body Scans from a Single Kinect -- Real-Time Hand Pose Estimation using Depth Sensors -- Part III: RGB-D Datasets -- A Category-Level 3D Object Dataset: Putting the Kinect to Work -- RGB-D Object Recognition: Features, Algorithms, and a Large Scale Benchmark -- RGBD-HuDaAct: A Color-Depth Video Database for Human Daily Activity Recognition."]
[{"$nulls":3},"Sommario/riassunto","The launch of Microsoft’s Kinect, the first high-resolution depth-sensing camera for the consumer market, generated considerable excitement not only among computer gamers, but also within the global community of computer vision researchers. The potential of "]
[{"$nulls":4},"consumer depth cameras extends well beyond entertainment and gaming, to real-world commercial applications such virtual fitting rooms, training for athletes, and assistance for the elderly. This authoritative text/reference reviews the scope and impact of this rapidly growing field, describing the most promising Kinect-based research activities, discussing significant current challenges, and showcasing exciting applications. Topics and features: Presents contributions from an international selection of preeminent authorities in their fields, from both academic and corporate research Addresses the classic problem of multi-view geometry of how to correlate images from different viewpoints to simultaneously estimate camera poses and world points Examines human pose estimation using video-rate depth images for gaming, motion capture, 3D human body scans, and hand pose recognition for sign language parsing Provides a review of approaches to various recognition problems, including category and instance learning of objects, and human activity recognition With a Foreword by Dr. Jamie Shotton of Microsoft Research, Cambridge, UK This broad-ranging overview is a must-read for researchers and graduate students of computer vision and robotics wishing to learn more about the state of the art of this increasingly “hot” topic."]