Ball Impact Localization via Moving Blur Detection
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Solution Overview
Problem
Existing techniques for ball impact localization in sports are costly, complex, and limited to large game fields, making them unsuitable for small courts with high ball speeds, and require continuous visibility of the ball, which is not feasible in all scenarios.
Innovation Solution
A device and method that use video input to detect moving blurs and calculate logical AND-operations between consecutive frames, allowing for ball impact localization without continuous visibility, suitable for implementation in embedded devices and scalable for various sports environments, including small courts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-speed cameras or multiple viewpoint cameras are used to ensure clear visibility of ball and target object, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent extracts only the essential information needed for impact localization from the video frames - specifically detecting moving blurs and calculating their trajectories. Instead of processing complete visual data from multiple cameras, the system focuses on extracting blur patterns and their motion vectors, which are sufficient for determining impact positions without requiring complex multi-camera coordination.
Solution Approach 2:
The patent employs a single camera system with standard frame rate instead of expensive high-speed or multi-viewpoint camera systems. The method processes ordinary video frames at standard rates, accepting that individual frames may not capture the ball clearly but that the sequence of frames provides sufficient trajectory information through blur analysis, thereby reducing hardware costs while maintaining localization accuracy.
2Measurement precision
If high-speed cameras are used to capture fast-moving ball in small courts, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent utilizes periodic video frames at standard frame rates to capture the ball's motion. Instead of requiring high-speed continuous capture, the system processes a sequence of periodic frames, detecting moving blurs in each frame and tracking their trajectories across frames. This periodic sampling approach is sufficient to determine impact positions in small courts with high ball speeds, eliminating the need for expensive high-speed cameras.
3Measurement precision
If video captures entire large game field, then measurement precision is improved for overall game analysis, but loss of time increases for capturing fast ball movement
Solution Approach 1:
The patent applies local quality analysis by focusing computational attention on specific regions where moving blurs are detected. Instead of processing the entire large game field uniformly, the system identifies and analyzes only the areas containing ball motion blur patterns. This localized processing approach maintains trajectory tracking accuracy while significantly reducing the time required to capture and process ball movement information.
4Measurement precision
If continuous visibility of ball is required for impact detection, then measurement precision is improved, but ease of operation decreases
Solution Approach 1:
The patent performs preliminary detection of moving blurs in video frames before the ball actually impacts the surface. By detecting the blur patterns and calculating trajectories in advance, the system can predict and identify impact positions even when the ball is not continuously visible or when the impact moment is captured as a blur rather than a sharp image. This preliminary analysis enables accurate impact detection without requiring continuous clear visibility of the ball.
Data Source
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AI summary
It is disclosed a method, and a device (10) capable of localizing ball impacts on a surface of an environment. Based on differences between any two consecutive video frames of the video, one or more blurs in the video are detected (704). Parameters of the ball are compared (706) with parameters of the detected one or more moving blurs. When the parameters being compared match, the moving blur for which the parameters match, is associated (708) with ball. Dimensions of the matching blur are determined (710). Based on a change in the dimensions of the moving blur, a ball impact is detected (712). Localizing (714) of the ball impact on a surface, is based on the change in the dimensions of the moving blur being associated with the ball, and environmental parameters. It is an advantage that localization of ball impacts does not require the ball to be continuously visible.