03606nam 2200637 a 450 991043760090332120200520144314.01-283-90966-91-4471-4640-910.1007/978-1-4471-4640-7(CKB)2670000000277594(EBL)1081753(OCoLC)813213128(SSID)ssj0000766971(PQKBManifestationID)11423965(PQKBTitleCode)TC0000766971(PQKBWorkID)10732523(PQKB)10598752(DE-He213)978-1-4471-4640-7(MiAaPQ)EBC1081753(PPN)168293986(EXLCZ)99267000000027759420121008d2013 uy 0engur|n|---|||||txtccrConsumer depth cameras for computer vision research topics and applications /Andrea Fossati ... [et al.], editors1st ed. 2013.London Springer20131 online resource (219 p.)Advances in computer vision and pattern recognition,2191-6586Description based upon print version of record.1-4471-4639-5 Includes bibliographical references and index.pt. 1. 3D registration and reconstruction -- pt. 2. Human body analysis -- pt. 3. RGB-D datasets.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 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.Advances in Computer Vision and Pattern Recognition,2191-6586Computer visionPhotogrammetryCamerasCalibrationComputer vision.Photogrammetry.CamerasCalibration.006.3006.3/7006.37Fossati Andrea267736MiAaPQMiAaPQMiAaPQBOOK9910437600903321Consumer depth cameras for computer vision4196632UNINA