Spatiotemporal Light Patterns for 3D Point Clouds in Moving Scenes
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Solution Overview
Problem
Existing 3D scanning techniques using time multiplexed light patterns face challenges in generating high-resolution point clouds for scenes with motion, requiring excessive memory and failing to combine images reliably due to relative movement between the scene and the projector or sensor.
Innovation Solution
The use of spatiotemporal light patterns, generated from a set of smaller light pattern tiles, allows for high-resolution 3D point cloud generation by integrating images with motion detection and adaptation, using reference pixels to solve the six degrees of freedom problem and combining stationary regions of the scene.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If time multiplexed light patterns are used to generate high-resolution point clouds, then measurement precision is improved, but device complexity increases and memory requirements become excessive
Solution Approach 1:
The patent divides the light pattern into multiple tiles that can be projected in different sequences. Instead of using a single complex time-multiplexed pattern, the system segments the pattern into manageable tiles (e.g., 4x4 grid) that can be independently controlled and combined, reducing overall system complexity while maintaining high measurement precision.
Solution Approach 2:
The system dynamically adapts the projection sequence based on detected motion in the scene. When motion is detected, the system adjusts which tiles are projected and in what order, allowing flexible adaptation to changing conditions without requiring a fixed complex projection schedule, thereby reducing device complexity.
2Measurement precision
If time multiplexed light patterns are used for scenes with motion, then measurement precision is improved, but reliability deteriorates due to relative movement between scene and projector
Solution Approach 1:
The system continuously monitors the scene for motion and dynamically adjusts the projection and capture process. When motion is detected between frames, the system adapts by selecting appropriate tile sequences and adjusting integration parameters, ensuring reliable point cloud generation even in dynamic scenes where static time-multiplexed approaches would fail.
Solution Approach 2:
The system uses feedback from motion detection to control the projection sequence and image integration process. By monitoring scene changes and adjusting the tile projection strategy accordingly, the system maintains reliable image integration despite relative movement between the scene and projector during capture.
3Measurement precision
If time multiplexed light patterns are used, then measurement precision is improved, but loss of time increases due to excessive memory access and processing
Solution Approach 1:
By segmenting the light pattern into tiles, the system can process and project smaller units independently. This reduces the memory access time required to load and process entire patterns, as only relevant tiles need to be accessed and processed at any given moment, thereby reducing time loss while maintaining high measurement precision through tile combination.
Data Source
AI summary
Methods, apparatus, systems, and articles of manufacture to generate 3D point clouds based on spatiotemporal light patterns are disclosed. A controller includes processor circuitry to execute the instructions to generate a series of light patterns based on a set of light pattern tiles. Each of the light pattern tiles is defined by a different arrangement of illuminated pixels. Each of the light patterns is defined by a different arrangement of the light pattern tiles. The processor circuitry is to instruct a projector to project the series of light patterns; instruct an image sensor to capture a series of images of reflections of the series of light patterns; and generate a three-dimensional point cloud based on the series of captured images.