With this method, new experimental results of hand-written recognition are obtained and stated in this paper. Also, Hidden Markov Models (HMM) is introduced and used as a tool to realize hand gesture classification. In our previous work, the effectiveness of different data processing methods including Fast Fourier Transform (FFT) and Discrete Cosine Transform (DCT) are compared, thus the latter, which is better, is adopted in this paper. During our experiments, although we write the characters in a plane, all the three-dimensional acceleration information is taken from muIMU in processing data as the third dimension is very helpful to be applied in practical application. The muIMU is built with three-dimensional accelerometer. Collectively, an average recognition time of 2.386 s was calculated with an average recognition rate of 97.37%.Ī Micro Inertial Measurement Unit (muIMU) based on Micro Electro Mechanical Systems (MEMS) sensor is applied to sense the motion information produced by human subjects.
Experiments were conducted in which different users were evaluated for their ability to navigate a PowerPoint presentation multiple times. Kinect takes the RGB data and depth data of the human skeleton and generates coordinate information corresponding to specific body joints. This method is implemented with the help of a depth sensor camera called Kinect. Next based on boundary values, such that if the hand crosses a boundary value of a given quadrant, then a SENDKEY stroke is generated that corresponds to that range. The proposed hand movement recognition technique primarily focuses on the direction of hand movement for dynamic recognition in real-time using least square fitting and virtual frame techniques. This paper proposes a novel assistive pointer device called Frontier Point method (FPM), which is based on a hand movement recognition technique. Basically, HCI provides a way for humans to interact with a computer using a keyboard, a mouse, and other input devices in real-time. From the disabled people perspective, there is huge demand to improve Human–Computer Interaction (HCI), to overcome their difficulty in using the standard interactive devices. In this modern era, the use of computer technology and computing devices play significant role in every day human activities. This method has shown promising result in real time environment. This variation of fingertip movements gives rise to the classification criteria for the numeric characters. Vertical movements can take place in upward or downward direction and horizontal movement can take place in rightward or leftward direction. For each frame the tip position is compared to the previous tip position to decide whether the movement is a vertical or horizontal movement. Numeric characters are detected by the finger movements made during the handwriting of the characters. In this paper a simple numeric character recognition algorithm has been proposed where colored fingertip has been used for the purpose of tracking. A numeric character recognition system is advantageous in a Human Computer Interaction system as it enables us to interact with a computer without a keyboard or other input devices. In the field of computer vision, numeric character recognition plays an important role for various applications such as in Human Computer Interaction system.
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