Depth Map Warping for Low-Latency Sensor Alignment
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Solution Overview
Problem
Depth maps and images from different sensors often require alignment, but existing methods struggle with latency and memory requirements, especially when sensors are separated in space, leading to misalignment and artifacts in the warped image.
Innovation Solution
The method involves warping a depth map to align with an image by transforming depth values from one sensor location to another, allowing for early start of the warping process before the original depth map is fully read, and making warped data available before completion, reducing latency and memory needs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If the depth map is warped after complete reading to ensure accuracy, then manufacturing precision is improved, but loss of time increases due to waiting for complete data
Solution Approach 1:
The patent applies preliminary action by starting the warping process before the depth map reading is complete. The system begins transforming depth values to image coordinates as soon as sufficient data is available, rather than waiting for complete reading. This reduces processing latency while maintaining alignment accuracy through iterative refinement as additional depth data becomes available.
Solution Approach 2:
The patent segments the warping process into independent pixel transformations that can be performed progressively. Each pixel's depth value is transformed to image coordinates independently, allowing the system to process and output results in stages rather than requiring complete data before any output. This enables early data availability while ensuring final accuracy.
2Manufacturing precision
If the entire depth map is read and stored before warping, then manufacturing precision is improved, but quantity of substance (memory usage) increases
Solution Approach 1:
The patent extracts only the necessary depth values needed for warping from the depth map, rather than requiring the entire depth map to be stored in memory. The system reads depth values progressively, transforms them to image coordinates, and outputs the warped image data. This extraction approach reduces memory requirements while maintaining alignment accuracy by processing only the relevant data portions.
3Adaptability or versatility
If warping is performed with sensor separation in space, then adaptability is improved for different sensor configurations, but object-generated harmful factors increase due to misalignment and artifacts
Solution Approach 1:
The patent applies parameter changes by transforming depth values using the relative spatial parameters between the depth sensor and image sensor. The system uses the known separation distance and angular relationships to calculate accurate transformations from depth map coordinates to image coordinates. This parameter-based transformation approach maintains alignment accuracy despite sensor separation, preventing artifacts while supporting flexible sensor configurations.
Data Source
AI summary
Methods, systems, and computer program products to warp a depth map into alignment with an image, where the image sensor (e.g., camera) responsible for the image and depth sensor responsible for an original depth map are separated in space. In an embodiment, the warping of the depth map may be started before the original depth map has been completely read. Moreover, data from the warped depth map may be made available to an application before the entire warped depth map has been completely generated. Such a method and system may improve the speed of the overall process and/or reduce memory requirements.