3D Golf Swing Tracking Using Depth Camera Histograms
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Solution Overview
Problem
Current methods for tracking golf swing movements, both marker-based and marker-less using image cameras, face challenges in accurately detecting body parts like hands and head in three-dimensional space, especially during complex golf swings, due to instability and sensitivity to light conditions.
Innovation Solution
A system utilizing a depth camera that extracts local histograms to classify body parts in depth images, employing a classifier trained with randomized forests to determine the three-dimensional positions of body parts, such as the head and hands, without the need for expensive tracking instruments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a marker-based tracking method is used to sense motion in three-dimensional space, then measurement precision is improved, but device complexity and cost increase due to expensive tracking instruments
Solution Approach 1:
The patent extracts and removes the marker component from the tracking system, transitioning from marker-based to marker-less tracking. This eliminates the need for expensive tracking instruments while maintaining the ability to track body part positions through image processing alone
Solution Approach 2:
The patent uses two-dimensional image copies from standard cameras to represent three-dimensional spatial information. By processing multiple 2D images from different angles and synthesizing depth information, the system achieves 3D tracking capability without requiring specialized 3D tracking equipment
2Device complexity
If a marker-less method using image cameras is used to track body parts, then device complexity is reduced, but measurement precision deteriorates due to limitations in tracking three-dimensional space and sensitivity to light conditions
Solution Approach 1:
The patent merges multiple 2D images from different camera angles to synthesize 3D spatial information. By combining image data from multiple perspectives, the system achieves accurate three-dimensional position tracking using only standard image cameras, overcoming the limitation of single-camera 2D tracking
Solution Approach 2:
The patent transforms two-dimensional image data into three-dimensional position information through image processing and depth estimation algorithms. This dimensionality conversion enables the system to track body parts in 3D space using 2D camera inputs, resolving the fundamental limitation of image camera-based tracking
3Measurement precision
If depth camera data is used to track body parts, then measurement precision and stability are improved, but device complexity increases compared to standard image cameras
Solution Approach 1:
The patent uses standard image cameras to create 2D image copies that are then processed to extract 3D position information. This approach creates a virtual depth map from conventional 2D images, achieving depth camera-like functionality without requiring actual depth sensing hardware
Data Source
AI summary
A position tracking apparatus includes: a depth image obtaining unit for obtaining a depth image; a database created by collecting depth images received from the depth image obtaining unit; a feature extracting unit for extracting features from each pixel of the depth image; a classifier training unit for training a classifier in order to determine the position of the parts of the body by receiving a feature set for each part of the body as inputs which are extracted by using the feature extracting unit from all of the depth images in the database; and a position determination unit for extracting features for each pixel of the depth image received by the depth image obtaining unit using the feature extracting unit in a state in which the classifier training unit trains the classifier, and for tracking the three-dimensional position of each part of the body through the classifier.