{"product_id":"computer-vision-and-machine-learning-with-rgb-d-sensors-9783319381053","title":"Computer Vision and Machine Learning with Rgb-D Sensors","description":"\u003cp\u003e • Author(s): Ling Shao\u003cbr\u003e • Publisher: Springer\u003cbr\u003e • Publisher Imprint: Springer\u003cbr\u003e • BISAC: Software Development \u0026amp; Engineering - Computer Graphics\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cb\u003eFrom the Back Cover\u003c\/b\u003e\u003cbr\u003e\u003c\/p\u003e\u003cp\u003eThe combination of high-resolution visual and depth sensing, supported by machine learning, opens up new opportunities to solve real-world problems in computer vision.\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eThis authoritative text\/reference presents an interdisciplinary selection of important, cutting-edge research on RGB-D based computer vision. Divided into four sections, the book opens with a detailed survey of the field, followed by a focused examination of RGB-D based 3D reconstruction, mapping and synthesis. The work continues with a section devoted to novel techniques that employ depth data for object detection, segmentation and tracking, and concludes with examples of accurate human action interpretation aided by depth sensors.\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cb\u003eTopics and features: \u003c\/b\u003e\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eDiscusses the calibration of color and depth cameras, the reduction of noise on depth maps, and methods for capturing human performance in 3D\u003c\/li\u003e\n\u003cli\u003eReviews a selection of applications which use RGB-D information to reconstruct human figures, evaluate energy consumption, and obtain accurate action classification\u003c\/li\u003e\n\u003cli\u003ePresents an innovative approach for 3D object retrieval, and for the reconstruction of gas flow from multiple Kinect cameras\u003c\/li\u003e\n\u003cli\u003eDescribes an RGB-D computer vision system designed to assist the visually impaired, and another for smart-environment sensing to assist elderly and disabled people\u003c\/li\u003e\n\u003cli\u003eExamines the effective features that characterize static hand poses, and introduces a unified framework to enforce both temporal and spatial constraints for hand parsing\u003c\/li\u003e\n\u003cli\u003eProposes a new classifier architecture for real-time hand pose recognition, and a novel hand segmentation and gesture recognition system\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003e\u003c\/p\u003eResearchers and practitioners working in computer vision, HCI and machine learning will find this to be a must-read text. The book also serves as a useful reference for graduate students studying computer vision, pattern recognition or multimedia","brand":"Springer","offers":[{"title":"Paperback","offer_id":45275116798103,"sku":"9783319381053","price":3633.0,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0666\/3471\/1191\/files\/9783319381053.webp?v=1769281944","url":"https:\/\/atlanticbooks.com\/products\/computer-vision-and-machine-learning-with-rgb-d-sensors-9783319381053","provider":"Atlantic Books","version":"1.0","type":"link"}