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Titlebook: Robust Hand Gesture Recognition for Robotic Hand Control; Ankit Chaudhary Book 2018 Springer Nature Singapore Pte Ltd. 2018 Image-based Ha

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樓主: 存貨清單
21#
發(fā)表于 2025-3-25 03:56:54 | 只看該作者
22#
發(fā)表于 2025-3-25 09:50:46 | 只看該作者
,Bent Fingers’ Angles Calculation, shape of the human hand is such that it is able to easily perform a number of otherwise tedious tasks. It can bend its fingers to different angles to pick up or to hold objects and to apply force via fingers or the palm area. In a number of scenarios, a human hand can perform the tasks much more ef
23#
發(fā)表于 2025-3-25 13:12:18 | 只看該作者
,Both Hands’ Angles Calculation,thod discussed in the previous chapter. There is a need to detect the angles for both hands to make the gesture-based system more robust. In this chapter, a novel method for angle approximation of both hands’ bent fingers is presented and its application to a robotic hand control is discussed. The s
24#
發(fā)表于 2025-3-25 17:10:49 | 只看該作者
Scientific Goals, invariant method to detect hand gesture in real time. ? Investigate a light intensity invariant method to detect hand gesture in real time. ? Explore automated techniques to calculate angles of bending fingers from hand gesture. ? Develop an automatic system to detect angles of fingers in motion.
25#
發(fā)表于 2025-3-25 21:19:32 | 只看該作者
26#
發(fā)表于 2025-3-26 03:07:33 | 只看該作者
27#
發(fā)表于 2025-3-26 04:51:43 | 只看該作者
28#
發(fā)表于 2025-3-26 09:47:14 | 只看該作者
Introduction,ognition (HGR) is the natural way of human–machine interaction. Today many researchers in the academia and industry are studying different techniques that make such interactions easier, natural, and convenient without the requirement for any additional devices.
29#
發(fā)表于 2025-3-26 14:40:18 | 只看該作者
30#
發(fā)表于 2025-3-26 17:10:39 | 只看該作者
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