Visual Tracking Psychological Quality Prediction of Multimedia Robot Images based on Analyzing Color Composition

Abstract

So far, there have been many examples of color composition visualization techniques combined with robot recognition. On this basis, this paper proposes a design method of visual tracking mental quality prediction system for visual processing and robots. Firstly, the system is analyzed and modeled. The SYSTEM uses a six-axis industrial robot AS an experimental platform, and uses exponential multiplication to model mental quality prediction. Through the correlation between rotation and pose matrix, the Jacobian matrix is derived, and the corresponding relationship between the robot terminal and the rotation speed composed of color is given. Then, according to the mathematical modeling of color composition and the selection of appropriate image characteristics, a kind of robot visual tracking psychological quality prediction control system based on positioning and image is constructed. Thus, the corresponding relationship between the feature points in the image and the rate of the color forming terminal can be determined. By using the method of differential mental quality prediction and speed transformation, the corresponding relation of each coordinate system in the mental quality prediction control of visual tracking is derived, and the motion rate in the color frame is transformed into the motion rate of each joint. At the same time, the visual servo system is analyzed in detail, and the visual servo control is developed. On this basis, the position based vision follow up and image tracking are studied, and a vision follow up controller for fast motion is proposed. The experimental results show that the fast feedforward control based on the fast feedback property of fast image proposed in this paper, and the experimental research on this basis, has strong practical significance.