Three-Camera Calibration for Broadcast and Tracking Camera Alignment
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Solution Overview
Problem
The challenge in tracking sports projectiles like golf balls involves calibrating a tracking sensor and a broadcast camera without the use of external reference markers or a wide base due to geometrical limitations, making it difficult to establish a transformation between their coordinate systems.
Innovation Solution
A method and apparatus using a third camera with overlapping fields of view to estimate transformations between the first and second camera systems, allowing for the relaxation of requirements on marker visibility and enabling accurate calibration by iteratively determining orientation and focal length components.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If external reference markers or a wide base are used for calibration, then measurement precision and transformation accuracy are improved, but device complexity and operational constraints increase
Solution Approach 1:
The patent extracts the calibration problem from the traditional approach requiring external markers and wide baseline setups. By using only the two cameras at arbitrary positions on the golf course without adding external reference objects, the solution removes the complexity of marker placement and measurement while still achieving accurate coordinate system transformation between the tracking camera and broadcast camera
Solution Approach 2:
The patent introduces an intermediary mathematical approach using corresponding points visible in both camera fields of view to establish the transformation. Instead of relying on physical markers, the method uses image processing to identify corresponding features (such as the golf ball position, terrain features, or other visible objects) and computes the transformation matrix through coordinate geometry, thereby mediating the calibration process without physical intermediaries
2Measurement precision
If external reference markers are added to the environment, then calibration accuracy is improved, but the golf course environment is modified and operational flexibility is reduced
Solution Approach 1:
The calibration system uses the existing environment and objects in the golf course itself as reference points. The cameras capture images of the same scene containing natural features (terrain, vegetation, golf course markings) that serve as self-provided reference points. This self-service approach eliminates the need to modify the environment with external markers while maintaining calibration capability
Solution Approach 2:
The calibration method is universally applicable to any golf course environment without requiring specific modifications. The same algorithm can be used regardless of the specific terrain, weather conditions, or course layout by simply identifying corresponding points in the captured images. This multi-functional approach allows the system to adapt to various environmental conditions while maintaining accurate calibration
3Measurement precision
If the distance between tracking camera and broadcast camera is increased, then transformation measurement is improved, but the geometrical limitations of the tee box are exceeded
Solution Approach 1:
The patent changes the calibration approach from relying on large physical baseline distance to using computational methods based on corresponding point matching. By transforming the problem from a geometric measurement challenge to an image processing and coordinate transformation problem, the system achieves accurate calibration even when cameras are positioned close together on the confined tee box area, effectively changing the critical parameter from physical distance to computational accuracy
4Ease of operation
If arbitrary camera placement is allowed, then operational ease is improved, but the ability to directly observe or measure orientation and translation transformations is reduced
Solution Approach 1:
The patent replaces the mechanical/physical measurement system with an optical-digital system. Instead of using physical rulers, theodolites, or mechanical alignment tools to directly measure camera orientations and positions, the system uses image capture and digital image processing to compute transformations. The mechanical measurement process is substituted with optical imaging followed by computational coordinate transformation based on corresponding points in the images
Data Source
Figure 1~2b
Figure 3
Figure 4~5a
AI summary
A system (100), a method and a calibration apparatus (110) for determining a first transformation (TAB) between a first coordinate system of a first camera (A) and a second coordinate system of a second camera (B) by use of a third camera (C). The third camera is required to capture a first and a second marker in its field of view. The calibration apparatus (110) iteratively determines updated orientation components of a third transformation (TAC), between the first and third cameras. In a similar manner, the calibration apparatus (110) iteratively determines updated orientation and translation components for a second transformation, between the first and second cameras. Furthermore, the calibration apparatus (110) iteratively determines at least updated orientation components for the first transformation.