Leveraging the Kinect Sensor to Correct Improper Bowling Form

Open Access
Article
Conference Proceedings
Authors: Brisaac JohnsonChris Crawford

Abstract: When we go to bowling alleys, more often than not, we are often mesmerized by the one person who seems to get astrike with every swing. Is it the way they swing the ball? Or is it due to their feet placement? However, the answeris more straightforward than one might think; the form we use to bowl can make a massive difference betweengetting a strike and getting a gutter ball. Having poor performance at this sport can make playing it frustrating andembarrassing due to the constant gutter balls and inconsistent swings. To increase the chance of getting a strike,proper form is needed to do so. In this paper, we propose an application, Bowler Correcter, that will correct the formof a bowler in real-time. To improve the form of a poor bowler, the Xbox Kinect sensor V2 was used to provide thenecessary adjustments to correct a bowler's form. To train the sensor with proper form, proficient bowlers providedtraining data to the sensor. When selecting bowlers with poor form, the following was observed in non-proficientbowlers during a screening: tensed shoulders, an improper swing of the ball, not crouching in the follow-throughstage, and skipping the stance stage. We capture the skeleton of the bowler instead of the movement, which allowsus to assess the form of the bowler more clearly and accurately. Since this is a complex gesture, it had to be split upinto three gestures that would be later stored in the bowling database - Follow Through, Stance, and Swing ArmBack; breaking this gesture into parts makes it easier for the sensor to detect and to provide better feedback. TheKinect SDK, along with the Kinect library, was used to provide the necessary drivers for the Kinect sensor andprovide the needed libraries for creating the application. When gathering training data for the sensor, the applicationKinect Studio was used; this application and the Visual Gesture Builder can be found in the Kinect SDK. To trainthe Kinect sensor, clips recorded in the Visual Gesture Builder are loaded into Kinect Studio, where each clip istagged where the stance is present. To test the effectiveness of the application, Sports Champion 2 for PlayStation 3using the PlayStation Eye and Move controller was used as the increase in popularity in AR and VR allowedparticipants to experience bowling without needing to travel to a bowling alley. Additionally, with Covid concerns,this provided a way of ensuring cleanliness, comfort, and the safety of our participants as they bowled. The bowlerswith poor form were asked to play two games of bowling, one game without the corrector and the other with thecorrector, with the difficulty level set to championship; this increased the sensitivity of the Move controller andremoved all aides that prevented the ball from going into the gutter. It was found that this application provided thenecessary feedback needed for poor bowlers to correct their form and improve their performance.

Keywords: body tracking, Human-Computer Interaction, posture corrector

DOI: 10.54941/ahfe1002142

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