AI Dart Hit Localization for Precise Target Scoring
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Solution Overview
Problem
Existing dart game systems struggle to accurately determine the location of dart pin hits on a target, often assigning the same score for different impact locations within the same segment, leading to inconsistencies in scoring.
Innovation Solution
A dart game system utilizing artificial intelligence technology, including a dart game apparatus with a camera unit, control unit, and a dart pin location identification network model, processes multiple images from different angles to precisely identify the hit location of dart pins and calculate scores accurately.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If coordinate information is assigned to segments for scoring, then scoring can be performed, but different impact locations within the same segment result in the same score
Solution Approach 1:
The dart target is divided into multiple segments with coordinate information, where each segment represents a specific scoring area. The system further segments the analysis by considering both segment-level scoring and precise hit location within segments, allowing differentiated scoring based on exact impact position while maintaining the segment structure for overall scoring organization.
Solution Approach 2:
The system applies different scoring qualities to different locations within the same segment by calculating precise hit coordinates. Instead of treating all hits in a segment equally, the system determines the exact position within the segment and applies appropriate scoring based on the local hit quality, thereby resolving the contradiction between segment-based simplicity and location-based precision.
2Device complexity
If a single camera captures the dart target, then the system is simpler, but accurate hit location identification becomes difficult
Solution Approach 1:
The system transitions from two-dimensional image analysis to three-dimensional spatial analysis by introducing multiple cameras at different angles. This dimensional expansion allows the system to accurately determine hit locations in three-dimensional space, resolving the limitation of single-camera systems while maintaining a relatively simple overall device architecture through the use of standard camera components.
Data Source
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AI summary
Disclosed is a method for providing a dart game, the method being performed by a dart game device, the method including: obtaining, in response to a first throw of a first dart pin, a first image corresponding to a dart target including the first dart pin; obtaining, in response to a second throw of a second dart pin, a second image corresponding to the dart target including the second dart pin; generating first location information of the first dart pin corresponding to the first image and second location information of the second dart pin corresponding to the second image by using an artificial intelligence-based dart pin location identification network model; and generating a play result for the dart game including the first throw and the second throw by using the first location information and the second location information.