Punch Anticipation in a Karate Combat with Computer Vision

Abstract

Fighting in karate martial art requires great dexterity and ability of multiple physical and psychological factors. A key and fundamental skill for the success of this endeavor is the anticipation of the opponent's movements. Anticipation is an innate attribute, but it can also be worked on with training. Vision training, in the search for peripheral vision that allows the opponent's body to be monitored, is continuously worked on in martial arts training. Nonetheless, peripheral vision can be of use outside the martial arts domain, such as when driving (to be able to notice the environment) or reading (to increase reading speed). New technologies can bring new training methods that enhance peripheral vision by training motion anticipation. For this, a tool designed for karate training is used to evaluate if computer vision filters can facilitate motion anticipation performance in karate practice. Our research aims to model the interaction of the fighters in order to improve the body reading of the opponent as well as the dexterity in the anticipation of the attacks made by the opponent, aimed to build a personalized system for psychomotor learning. A user study is carried out to evaluate whether computer vision can be used to improve the prediction of punch attacks launched by the rival as well as the response time to them.