Optimizing Hand Gesture Recognition:

CHF 76.35
Auf Lager
SKU
RQ2H39UJ4EB
Stock 1 Verfügbar
Geliefert zwischen Mi., 25.02.2026 und Do., 26.02.2026

Details

One very interesting field of research in Pattern Recognition that has gained much attention in recent times is Gesture Recognition. Gesture may be described as the manner in which a person moves his body and limbs to express an idea or sentiment. People frequently use gestures to communicate in their day-to-day life. Therefore, gestures are a natural means of conveying information. This has motivated to use gestures for communicating with computers. Thus, gestures provide an attractive and user-friendly alternative to interface devices like keyboard, mouse and joysticks in human-computer interaction (HCI). Accordingly, the basic aim of gesture recognition research is to build a system which can identify/interpret specific human gestures automatically and use them to convey information.The main objective of this book is to study methods based on state-of-the-art techniques. The thesis addresses to the development of hand gesture recognition using Video Object Plane Generation Hand Segmentation, Modified Finite State Machine (MFSM), Modified Hidden Markov Model (MHMM) and Dynamic Time Warping (DTW).

Autorentext
Dr. (Mrs) Ketki Prashant Kshirsagar completed her B.E. in Electronic and Telecommunication Engineering from Walchand Institute of Technology, Shivaji University, Kolhapur and M. Tech in Electronics and Ph.D from Shri Guru Gobind Singhji Institute of Engineering and Technology, Nanded , Swami Ramanand Teerth Marathwada University.

Weitere Informationen

  • Allgemeine Informationen
    • GTIN 09786208064327
    • Genre Mechanical Engineering
    • Sprache Englisch
    • Anzahl Seiten 96
    • Herausgeber LAP LAMBERT Academic Publishing
    • Größe H220mm x B150mm x T6mm
    • Jahr 2024
    • EAN 9786208064327
    • Format Kartonierter Einband
    • ISBN 6208064325
    • Veröffentlichung 02.09.2024
    • Titel Optimizing Hand Gesture Recognition:
    • Autor Ketki Prashant Kshirsagar
    • Untertitel Enhanced Methods Using MFSM, MHMM, and DTW
    • Gewicht 161g

Bewertungen

Schreiben Sie eine Bewertung
Nur registrierte Benutzer können Bewertungen schreiben. Bitte loggen Sie sich ein oder erstellen Sie ein Konto.
Made with ♥ in Switzerland | ©2025 Avento by Gametime AG
Gametime AG | Hohlstrasse 216 | 8004 Zürich | Schweiz | UID: CHE-112.967.470
Kundenservice: customerservice@avento.shop | Tel: +41 44 248 38 38