Depth Map Dynamic Range Extension via Multi-Intensity Capture
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Solution Overview
Problem
Existing depth map technologies face challenges in accurately capturing depth information across varying light intensities and sensor integration times, leading to pixel saturation and difficulties in distinguishing depth differences, especially when objects are close or far from the light sensor, and when dealing with reflective, semi-transparent, or transparent surfaces.
Innovation Solution
The method involves capturing initial and subsequent images at different light intensity levels and sensor integration times, dynamically adjusting light intensities and integration times based on pixel saturation, and synthesizing these images using high dynamic range imaging techniques to generate a combined depth map that preserves information from both near and far objects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single light intensity level is used for depth mapping, then the system is simple to operate, but pixel saturation occurs for close objects and far objects cannot be distinguished
Solution Approach 1:
The imaging process is segmented into multiple captures at different light intensity levels. Close objects are captured with lower intensity to avoid saturation, while far objects are captured with higher intensity to ensure sufficient signal, then the segments are merged into a unified depth map.
Solution Approach 2:
The system dynamically adjusts light intensity levels between captures based on detected pixel saturation. When saturation is detected in certain regions, the intensity for subsequent captures is reduced for those regions, allowing adaptive optimization without manual intervention.
2Reliability
If high light intensity is used to capture far objects, then far objects are visible, but close objects become saturated
Solution Approach 1:
Different light intensity levels are applied locally to different regions of the scene based on distance. Close objects receive lower intensity to prevent saturation while far objects receive higher intensity to ensure detection, with each region optimized independently.
Solution Approach 2:
The patent converts the harmful effect of pixel saturation into useful information by detecting saturated pixels and using them to guide subsequent captures at lower intensity levels, transforming a failure mode into a control signal for optimization.
3Measurement precision
If multiple images at different light intensities are captured and synthesized, then dynamic range is extended, but processing time increases
Solution Approach 1:
The system performs preliminary analysis of captured images to detect pixel saturation and determine which regions require additional captures. This preliminary action guides subsequent imaging efforts, avoiding unnecessary captures and reducing overall processing time.
Solution Approach 2:
The system performs captures selectively only where needed based on saturation detection, rather than uniformly capturing all regions multiple times. This partial action approach reduces total processing time while maintaining depth map accuracy where it matters most.
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 extends the dynamic range of depth maps, providing more accurate distance determination and overcoming issues of pixel saturation, allowing for better detection and tracking of objects regardless of their proximity or surface properties.
Implementation Method 1
Time of flight techniques may determine distances to objects within an environment by timing how long it takes for light transmitted from a light source to travel to the objects and reflect back to an image sensor
Implementation Method 2
Structured light illumination involves projecting a light pattern into an environment, capturing an image of the reflected light pattern, and then determining distance information from the spacings and/or distortions associated with the reflected light pattern relative to the projected light pattern
Data Source
AI summary
A method for extending the dynamic range of a depth map by deriving depth information from a synthesized image of a plurality of images captured at different light intensity levels and/or captured over different sensor integration times is described. In some embodiments, an initial image of an environment is captured while the environment is illuminated with light of a first light intensity. One or more subsequent images are subsequently captured while the environment is illuminated with light of one or more different light intensities. The one or more different light intensities may be dynamically configured based on a degree of pixel saturation associated with previously captured images. The initial image and the one or more subsequent images may be synthesized into a synthesized image by applying high dynamic range imaging techniques.