Depth Camera Adaptive Pixel Sampling for Sparse Data Resolution
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Solution Overview
Problem
Existing distance measuring devices using time-of-flight techniques with single photon avalanche diodes face challenges in generating high-resolution depth images from sparse depth information, as accuracy deteriorates based on pixel positions.
Innovation Solution
A distance measuring device and system that includes a light receiving unit with multiple pixels, a high-resolution processing unit to generate high-resolution depth images from sparse data, and a position determination unit that determines active pixels based on edge information from the high-resolution depth images, allowing for improved accuracy by adaptively sampling and avoiding object edges.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If resolution of depth image is increased by using more pixels, then depth information becomes denser, but device complexity and cost increase
Solution Approach 1:
The patent divides the pixel array into multiple regions with different sampling densities. High-resolution regions correspond to object areas with edges or important features, while low-resolution regions correspond to background or uniform areas. This segmentation allows the system to achieve high effective resolution where needed while maintaining low overall device complexity.
Solution Approach 2:
The patent applies different sampling qualities to different spatial locations based on local image characteristics. Edge detection algorithms identify regions requiring high resolution, and the system dynamically adjusts pixel activation patterns to provide high sampling density in those regions while using sparse sampling in other areas, optimizing the trade-off between resolution and complexity.
2Measurement precision
If sampling density is increased to improve depth measurement accuracy, then measurement precision improves, but use of energy increases
Solution Approach 1:
The patent implements dynamic pixel activation where the sampling pattern changes over time based on detected object features. The system initially captures data from all pixels, identifies edge regions, and then selectively activates only the necessary pixels for subsequent measurements. This dynamic adaptation maintains measurement precision in critical areas while dramatically reducing overall energy consumption.
Solution Approach 2:
The patent applies partial sampling strategies where only a subset of pixels is actively used at any given time. By identifying and focusing computational resources and energy on only the portions of the scene that require high precision (edge regions), the system achieves sufficient measurement accuracy without the excessive energy cost of uniform high-density sampling across the entire field of view.
3Stability of the object's composition
If uniform sampling is applied across all pixel positions, then measurement consistency is maintained, but measurement precision deteriorates at certain pixel positions
Solution Approach 1:
The patent deliberately introduces asymmetric sampling patterns that adapt to the asymmetric distribution of important features in the scene. Rather than uniform sampling, the system concentrates sampling resources asymmetrically toward regions containing object edges and boundaries, accepting lower precision in symmetric background regions to achieve superior overall measurement quality where it matters most.
Solution Approach 2:
The patent performs preliminary edge detection and feature identification before final depth measurement. This preliminary action allows the system to pre-determine which pixel positions require high-precision sampling, enabling subsequent measurements to be optimized for those specific locations rather than applying uniform sampling that would waste resources or miss critical details.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables the generation of high-resolution depth images with enhanced accuracy by selectively activating pixels and adjusting sampling positions, thereby improving the resolution and reliability of depth measurements.
Implementation Method 1
distance measuring devices (hereinafter referred to as depth cameras) that use a time-of-flight (ToF) technique to measure a distance
Implementation Method 2
Some depth cameras use a single photon avalanche diode (SPAD) for a light receiving pixel. In a depth camera using a SPAD, avalanche amplification occurs when one photon enters a PN junction region with a high electric field
Data Source
AI summary
The present technology relates to a distance measuring device, a method for controlling the same, and a distance measuring system that allow for generation of a high-resolution depth image with high accuracy from sparse depth information. The distance measuring device includes: a light receiving unit that has a plurality of pixels that receive reflected light obtained from irradiation light reflected by an object; a high-resolution processing unit that generates a high-resolution depth image from a sparse depth image acquired by the light receiving unit; and a position determination unit that determines an active pixel in which a light receiving operation is performed in the light receiving unit on the basis of edge information of the high-resolution depth image. The present technology can be applied to, for example, a distance measuring system or the like that detects a distance to a subject in a depth direction.