Structured Light 3D Reconstruction Using Adaptive Spatio-Temporal Decoding
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Solution Overview
Problem
Conventional single-shot structured light methods decrease spatial resolution and perform poorly near depth discontinuities, and are not motion-sensitive, as they project the same pattern repeatedly for each image, even for static or slowly moving scenes.
Innovation Solution
A method and system that project a set of sequentially shifted striped patterns, using adaptive spatio-temporal windows for decoding, which reduces the spatial neighborhood required for decoding and improves reconstruction quality near depth discontinuities by leveraging both spatial and temporal information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional single-shot structured light methods project the same pattern repeatedly for each image, then the decoding process is simplified, but the spatial resolution decreases and reconstruction quality deteriorates near depth discontinuities
Solution Approach 1:
The patent applies dynamics by making the decoding window size adaptive rather than fixed. The spatial-temporal decoding window dynamically adjusts its size based on local scene characteristics, allowing larger windows in homogeneous regions and smaller windows near depth discontinuities. This dynamic adaptation resolves the contradiction by maintaining decoding simplicity while improving spatial resolution and reconstruction quality at critical locations.
Solution Approach 2:
The patent implements local quality by applying different decoding window sizes to different spatial locations. Instead of using a uniform decoding approach across the entire image, the method selectively adjusts the decoding window size based on local scene properties, such as motion magnitude and depth discontinuity detection. This allows the system to maintain high spatial resolution where needed while preserving decoding efficiency in other regions.
2Device complexity
If conventional single-shot methods use fixed pattern projection for all images, then processing each image independently is straightforward, but the methods are not motion-sensitive and reconstruction quality suffers in dynamic scenes
Solution Approach 1:
The patent makes the decoding process motion-sensitive by dynamically adjusting the spatial-temporal decoding window based on detected motion. The system analyzes temporal variations in the projected patterns and adapts the decoding window size accordingly, allowing it to handle both static and dynamic scenes effectively. This dynamic approach maintains reasonable processing complexity while significantly improving adaptability to motion.
Solution Approach 2:
The patent changes the decoding parameters (window size) based on scene conditions. By monitoring temporal changes in the projected patterns and adjusting the decoding window size accordingly, the system adapts its processing behavior to match the actual scene dynamics. This parameter adaptation resolves the contradiction between processing complexity and motion sensitivity.
3Stability of the object's composition
If conventional methods use fixed-size spatial windows for decoding, then the decoding process is consistent, but the effective size of spatial neighborhood cannot be reduced even when using multiple patterns
Solution Approach 1:
The patent resolves this contradiction by making the decoding window size dynamic rather than fixed. The spatial-temporal decoding window adapts its size based on local scene characteristics and motion detection, allowing the system to reduce the effective spatial neighborhood size in appropriate regions while maintaining decoding consistency through a systematic adaptation process.
Solution Approach 2:
The patent introduces the temporal dimension to the decoding process by using spatio-temporal decoding windows. This allows the system to leverage information from multiple time points, effectively reducing the required spatial neighborhood size while maintaining or improving decoding accuracy. The temporal dimension provides additional degrees of freedom for decoding that compensate for reduced spatial window sizes.
4Measurement precision
If the entire scene is assumed to be static during projection of all shifted patterns, then spatial resolution can be improved by pixel-shifting, but this requirement is too restrictive for practical dynamic scene reconstruction
Solution Approach 1:
The patent applies local quality by allowing different regions of the scene to have different motion characteristics. Instead of requiring the entire scene to be static, the method processes regions independently with adaptive decoding windows that account for local motion. This allows high spatial resolution to be achieved in static or slowly moving regions while tolerating motion in other parts of the scene.
Solution Approach 2:
The patent makes the system dynamic by adapting the decoding process to actual scene motion rather than assuming static conditions. The spatio-temporal decoding window size is adjusted based on detected motion in different regions, allowing the system to maintain high spatial resolution where the scene is static while accommodating motion where it occurs.
Data Source
AI summary
A structured light pattern including a set of patterns in a sequence is generated by initializing a base pattern. The base pattern includes a sequence of colored stripes such that each subsequence of the colored stripes is unique for a particular size of the subsequence. The base pattern is shifted hierarchically, spatially and temporally a predetermined number of times to generate the set of patterns, wherein each pattern is different spatially and temporally. A unique location of each pixel in a set of images acquired of a scene is determined, while projecting the set of patterns onto the scene, wherein there is one image for each pattern.