A Gesture Recognition Algorithm Using Hausdorff-Like Distance Template Matching Based on the Main Direction of Gesture

2015 ◽  
Vol 713-715 ◽  
pp. 2156-2159 ◽  
Author(s):  
Xue Wen Yang ◽  
Zhi Quan Feng ◽  
Zhong Zhu Huang ◽  
Na Na He
Keyword(s):  
Coordinate System ◽  
Gesture Recognition ◽  
Template Matching ◽  
Recognition Rate ◽  
Video Stream ◽  
Recognition Algorithm ◽  
Main Direction ◽  
Hand Gesture ◽  
Rectangular Coordinate System ◽  
Image Area

Hand gesture of rotation, scaling and translation is the key problem of gesture recognition. This paper proposes a gesture recognition algorithm based on Hausdorff-like distance template matching of gesture main direction. Firstly, we segment hand gesture from video stream. Secondly, we calculate the main direction of gesture in the image, and build a 2D rectangular coordinate system. Then, we clockwise divide the gesture into eight sub-image area along the main direction of gesture and calculate the coordinates of target pixel points in each sub-image area in the 2D rectangular coordinate system. Finally, the algorithm of Hausdorff-like distance template matching is used to recognize the final gesture. Experimental results show that this algorithm can achieve real-time correct recognition of gestures in relatively stable light conditions. The overall recognition rate can reach 95%.

Fusion of Image Contour Moments and Fourier Descriptors for the Hand Gesture Recognition

2012 ◽  
Vol 433-440 ◽  
pp. 5188-5192
Author(s):  
Hai Long Lei ◽  
Sheng Yang
Keyword(s):  
Gesture Recognition ◽  
Recognition Rate ◽  
Recognition Algorithm ◽  
Hand Gesture Recognition ◽  
Hand Gesture ◽  
Fourier Descriptor ◽  
Bp Network ◽  
Moment Invariant ◽  
Hand Shape ◽  
Image Contour

Hand is a highly variable organ and hand features are easily affected by environmental factors. Considering the characteristics of hand gesture, a novel hand gesture recognition algorithm based on hybrid moments is presented. First, According to the color cue, the hand shape is available to extract from the complicated background, then the contour moment invariant and Fourier Descriptor are extracted and fused into a hybrid feature, finally the hybrid feature are put into the BP network to identity. The experimental results show that the method has better robustness and higher recognition rate.

Human action recognition using simple geometric features and a finite state machine

2013 ◽  
Vol 18 (2-3) ◽  
pp. 49-60 ◽  
Author(s):  
Damian Dudzńiski ◽  
Tomasz Kryjak ◽  
Zbigniew Mikrut
Keyword(s):  
Action Recognition ◽  
Finite State Machine ◽  
Recognition Rate ◽  
Human Action Recognition ◽  
Human Action ◽  
Video Stream ◽  
State Machine ◽  
Recognition Algorithm ◽  
Finite State ◽  
Correct Recognition Rate

Abstract In this paper a human action recognition algorithm, which uses background generation with shadow elimination, silhouette description based on simple geometrical features and a finite state machine for recognizing particular actions is described. The performed tests indicate that this approach obtains a 81 % correct recognition rate allowing real-time image processing of a 360 X 288 video stream.

Hand Gesture Recognition Algorithm: A Real-Time Human-Body-Based Approach

2013 ◽  
Vol 303-306 ◽  
pp. 1338-1343
Author(s):  
Xin Xiong Li ◽  
Yi Xiong ◽  
Zhi Yong Pang ◽  
Di Hu Chen
Keyword(s):  
Real Time ◽  
Gesture Recognition ◽  
Human Body ◽  
Skin Color ◽  
Average Rate ◽  
Vital Role ◽  
Recognition Algorithm ◽  
Hand Gesture Recognition ◽  
High Tech ◽  
Hand Gesture

Despite the appearance of high-tech human computer interface (HCI) devices, pattern recognition and gesture recognition with single camera are still playing vital role in research. A real-time human-body based algorithm for hand gesture recognition is proposed in this paper. The basis of our approach is a combination of moving object segmentation process and skin color detector based on human body structure to obtain the moving hands from input images, which is able to deal with the problem of complex background and random noises, and a rotate correction process for better finger detection. With ten fingers detected, more than 1000 gestures can be recognized before concerning motion paths. This paper includes experimental results of five gestures, which can be extended to other conditions. Experiments show that the algorithm can achieve a 99 percent recognition average rate and is suitable for real-time applications.

A Real Time Hand Gesture Recognition System Based on DFT and SVM

2013 ◽  
Vol 284-287 ◽  
pp. 3004-3009 ◽  
Author(s):  
Wen Her Chen ◽  
Ching Tang Hsieh ◽  
Tsun Te Liu
Keyword(s):  
Gesture Recognition ◽  
Skin Color ◽  
Recognition System ◽  
Extraction Process ◽  
Recognition Algorithm ◽  
Hand Gesture Recognition ◽  
Hand Gesture ◽  
Fast Detection ◽  
Starting Point ◽  
Boundary Deformation

Vision based band gesture recognition provides a more nature and powerful means for human-computer interaction. A fast detection process of hand gesture and an effective feature extraction process are presented. The proposed a hand gesture recognition algorithm comprises four main steps. First use Cam-shift algorithm to track skin color after closing process. Second, in order to extract feature, we use BEA to extract the boundary of the hand. Third, the benefits of Fourier descriptor are invariance to the starting point of the boundary, deformation, and rotation, and therefore transform the starting point of the boundary by Fourier transformation. Finally, outline feature for the nonlinear non-separable type of data was classified by using SVM. Experimental results showed the accuracy is 93.4% in average and demonstrated the feasibility of proposed system.

scholarly journals Hand Gesture Recognition Using PCA, KNN and SVM

2019 ◽  
pp. 547-550
Author(s):  
Julakanti Likhitha Reddy ◽  
Bhavya Mallela ◽  
Lakshmi Lavanya Bannaravuri ◽  
Kotha Mohan Krishna
Keyword(s):  
Gesture Recognition ◽  
Skin Color ◽  
Template Matching ◽  
Hand Gesture Recognition ◽  
Support Vector ◽  
Hand Gesture ◽  
Color Model ◽  
Language Recognition ◽  
Sign Language Recognition ◽  
Skin Color Model

To interact with world using expressions or body movements is comparatively effective than just speaking. Gesture recognition can be a better way to convey meaningful information. Communication through gestures has been widely used by humans to express their thoughts and feelings. Gestures can be performed with any body part like head, face, hands and arms but most predominantly hand is use to perform gestures, Hand Gesture Recognition have been widely accepted for numerous applications such as human computer interactions, robotics, sign language recognition, etc. This paper focuses on bare hand gesture recognition system by proposing a scheme using a database-driven hand gesture recognition based upon skin color model approach and thresholding approach along with an effective template matching with can be effectively used for human robotics applications and similar other applications .Initially, hand region is segmented by applying skin color model in YCbCr color space. Y represents the luminance and Cb and Cr represents chrominance. In the next stage Otsu thresholding is applied to separate foreground and background. Finally, template based matching technique is developed using Principal Component Analysis (PCA), k-nearest neighbour (KNN) and Support Vector Machine (SVM) for recognition. KNN is used for statistical estimation and pattern recognition. SVM can be used for classification or regression problems.

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