Shuying Zhao

Design and implementation of human-robot interactive demonstration system based on Kinect

With the development of technology, humanoid robots gradually enter our life, not only for education, but helping people with housework and many other tasks, some of which are inevitable for human. But only few people know how to control and interact with a humanoid robot, which hinders the development of humanoid robot. So a human-robot interactive demonstration system is designed to help non-expert users to control the humanoid robot, Aldebaran humanoid robot Nao in this case. Users just need to use the most natural body gestures to interact with the robot. Microsoft Kinect is applied in this system to recognize different body gestures and generate visual Human-Robot interaction interface, then the controlling signals of different body gesture modules are sent to Nao through wifi, which can stimulate Nao to complete tasks. This kind of system aims to enrich the interactive way between human and robots and help non-expert users to control the robot freely, making Human-Robot interaction much easier.

Dynamic hand gesture recognition using motion trajectories and key frames

In this paper, we address the problem of dynamic hand gesture recognition from unaided video sequences. We present a novel approach based on motion trajectories of hands and hand shapes of the key frames. Firstly, the hand area is segmented by active skin color model. Then the hand motion trajectories are extracted with dynamic time warping(DTW) algorithm and the key frame of video sequences is computed by frames difference. The hand gesture of the key frame is considered as a static hand gesture. The feature of hand shape is represented with Fourier descriptor and recognized by neural network. The combined method of the motion trajectories and key frame is presented to recognize the dynamic hand gesture from unaided video sequences. Experimental results show that the proposed approach is capable of effectively recognizing the dynamic hand gesture.

A novel interactive method of virtual reality system based on hand gesture recognition

Hand gesture is a natural and intuitive interactive method. This paper presents a novel interactive method of virtual reality system based on hand gesture recognition. The hand gesture segmentation method is proposed based on building complexion model by Gaussian distribution and the background model by automatically update the background parameters to improve the ability of adaptation environment. According to the good describing ability of Fourier Descriptor and the good self-learning ability of BP neural network, an improved algorithm of hand recognition is presented. Experiment result indicates that this method is flexible, realistic and exact, and fit for many virtual reality systems.

Hand extraction using geometric moments based on active skin color model

The hand gesture is the most common and natural way for human daily interaction. In this paper, we propose a novel approach to hand extraction based on active skin color model. The skin color model is first built by the non-linear transformation in YCbCr color space. Then the obtained model is applied to hand segmentation. Hand feature is extracted by calculating the seven moments of hand segmentation image. The experimental results demonstrate the feasibility of the proposed method.

Algorithm of location of chess-robot system based on computer vision

This paper demonstrates the principle of the robot chess system based on computer vision. According to improved Hough transform, a new image recognition method was proposed to settle the problem of the location in the robot chess system. Application results show that this method has the high performances in robustness, speed and accuracy.

Recognition of dynamic hand gesture based on SCHMM model

Dynamic gesture recognition is a key issue for visual gesture-based human-computer interaction. In this paper, a dynamic gesture recognition method is proposed based on SCHMM to solve the problem, which DHMM method is high speed and low rate and CHMM method is low speed and high rate. And the gesture clustering analysis, Baum—Welch algorithm of parametric estimation and Viterbi recognition algorithm is studied. Experiment result is given to show the balance performance of recognition rate and speed and the algorithm is satisfied for applications.

Fingerprint image segmentation method based on normal distribution model

In this paper, the advantages and disadvantages of the gray variance directional image segmentation methods were analyzed. On the base of gray normalization, a new approach to segment the fingerprint images was proposed using the normal distribution model of the fingerprint image graypsilas character. This approach makes use of the gray characters of the local and global images. Meanwhile, it has the advantage to choose the threshold automatic without the experience. The experimental results show that the method for the fingerprint image segmentation is effective, adaptive and quick and it can meet the need of fingerprint recognition system.

Nao humanoid robot gait planning based on the linear inverted pendulum

The gait planning of humanoid robot Nao is solved based on the linear inverted pendulum (LIPM) in this paper. The step length and period is selected according to the structure of Nao. LIPM model and ZMP is applied in the planning. An ideal gait data is obtained through simulation experiment, demonstrating the effectiveness of the LIPM model in the gait planning of the biped robot.

Target recognition and localization of international standard platform humanoid robot

According to the rules of Chinese robot competition and RoboCup open standard platform league competition, the problem of the target recognition and localization with the NAO robot need to be solved. Through setting white balance of the robots vision sensor, the images are processed and thresholds segmentation is got. Then the outline of the target can be got and the centroid is calculated. Thus the position of the target is located by structuring the geometric relation model between robot and targets.

Research on Robotic Popular Science System Based on LEGO Bricks

The robotic technology is one of the hottest topic. With the increasingly wide range of applications in people¿s daily life, popularizing knowledge of robotic technology has become an important content of popular science. This paper researches autonomous navigation, visual identification, man-machine interaction and so on. According this, the robotic science educational systems with rectangular coordinates are designed using LEGO component. The experiment results show that the robotics¿ science educational system operated stably and reliably. It provides a novel approach to science education of robotics technology.