Development Of A Vision-based Home Somatosensory Dart Target System

Nowadays,people’s economic level is gradually improving,people’s quality of life is also improved,so people’s demand for entertainment products is growing.At the same time,with the rapid development of science and technology,the rapid development of computer technology,intelligent products gradually enter people’s lives.In recent years,artificial intelligence has gradually entered people’s life,computer vision technology has become more and more popular,there are various intelligent entertainment devices in the market,and the sense of body game machine is deeply loved by everyone.Dart sport is an ancient sport.At present,dart game equipment in the market is still in the stage of traditional equipment.According to the current market situation and the development trend of science and technology,this paper designs a home use body sense dart target system.In this design,computer vision technology is applied to realize the body sense operation and discard the throwing objects in the traditional darts,so that the darts game becomes convenient,safe and improves its entertainment.In this paper,based on the analysis of the demand for home-use darts target system,the somatosensory dart target system is designed,and the system is divided into four units,namely: main controller,image acquisition unit,information output unit and power supply unit.This paper first analyzes the requirements and performance indicators of home somatosensory dart targets,determines the overall design plan,selects Intel’s Realsense D435 camera and Up board development board as the image acquisition unit and main control chip,and uses this to the system Select other hardware to build the actual system.Then design the recognition algorithm,use computer vision technology to determine the throwing accuracy of the thrower by judging the throwing attitude of the thrower.Finally,program the system,realize its functions,and debug the functions of the system.Experiments show that the system can determine the body posture after the end of throwing through the relative position relationship between the hand and the head in the image,and determine the accuracy of throwing based on this,and then give the corresponding score.The system functions well and achieve the expected results.