Normal view MARC view ISBD view

Kinesthetic Perception [electronic resource] : A Machine Learning Approach /

By: Chaudhuri, Subhasis [author.].
Contributor(s): Bhardwaj, Amit [author.] | SpringerLink (Online service).
Series: Studies in Computational Intelligence: 748Publisher: Singapore : Springer Singapore : Imprint: Springer, 2018Edition: 1st ed. 2018.Description: XV, 138 p. 50 illus., 44 illus. in color. | Binding - Card Paper |.Content type: text Media type: computer Carrier type: online resourceISBN: 9789811066924.Subject(s): Computer Engineering | Robotics and Automation | Artificial Intelligence | Control and Systems TheoryDDC classification: 629.892 Online resources: Click here to access eBook in Springer Nature platform. (Within Campus only.) In: Springer Nature eBookSummary: This book focuses on the study of possible adaptive sampling mechanisms for haptic data compression aimed at applications like tele-operations and tele-surgery. Demonstrating that the selection of the perceptual dead zones is a non-trivial problem, it presents an exposition of various issues that researchers must consider while designing compression algorithms based on just noticeable difference (JND). The book begins by identifying perceptually adaptive sampling strategies for 1-D haptic signals, and goes on to extend the findings on multidimensional signals to study directional sensitivity, if any. The book also discusses the effect of the rate of change of kinesthetic stimuli on the JND, temporal resolution for the perceivability of kinesthetic force stimuli, dependence of kinesthetic perception on the task being performed, the sequential effect on kinesthetic perception, and, correspondingly, on the perceptual dead zone. Offering a valuable resource for researchers, professionals, and graduate students working on haptics and machine perception studies, the book can also support interdisciplinary work focused on automation in surgery.
List(s) this item appears in: Springer Nature eBooks
Tags from this library: No tags from this library for this title. Log in to add tags.
    average rating: 0.0 (0 votes)
No physical items for this record

This book focuses on the study of possible adaptive sampling mechanisms for haptic data compression aimed at applications like tele-operations and tele-surgery. Demonstrating that the selection of the perceptual dead zones is a non-trivial problem, it presents an exposition of various issues that researchers must consider while designing compression algorithms based on just noticeable difference (JND). The book begins by identifying perceptually adaptive sampling strategies for 1-D haptic signals, and goes on to extend the findings on multidimensional signals to study directional sensitivity, if any. The book also discusses the effect of the rate of change of kinesthetic stimuli on the JND, temporal resolution for the perceivability of kinesthetic force stimuli, dependence of kinesthetic perception on the task being performed, the sequential effect on kinesthetic perception, and, correspondingly, on the perceptual dead zone. Offering a valuable resource for researchers, professionals, and graduate students working on haptics and machine perception studies, the book can also support interdisciplinary work focused on automation in surgery.

There are no comments for this item.

Log in to your account to post a comment.
Unique Visitors hit counter Total Page Views free counter
Implemented and Maintained by AIKTC-KRRC (Central Library).
For any Suggestions/Query Contact to library or Email: librarian@aiktc.ac.in | Ph:+91 22 27481247
Website/OPAC best viewed in Mozilla Browser in 1366X768 Resolution.

Powered by Koha