Depth Map Estimation Using Time of Flight Histograms
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Solution Overview
Problem
Current combinations of stereoscopic determination and time of flight measurement techniques require high-resolution, bulky, and costly sensors, which are not compatible with compact, battery-powered autonomous on-board technologies, and result in long calculation times and errors due to high computational resource demands.
Innovation Solution
A method that generates a depth map using histograms of distances acquisition zone by acquisition zone, optimizing stereoscopic processing by incorporating time of flight measurements, which reduces calculation complexity and enhances reliability, allowing for improved spatial understanding of a scene compatible with autonomous or on-board systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-resolution time of flight sensors are used to improve depth map determination accuracy, then measurement precision is improved, but device complexity, size, and cost increase
Solution Approach 1:
The patent segments the scene into multiple acquisition zones and processes each zone independently using histograms. This allows lower-resolution time of flight sensors to effectively capture depth information by dividing the measurement space, resolving the contradiction between sensor resolution and measurement precision.
Solution Approach 2:
The patent introduces histograms as an additional dimensional representation of depth data. Instead of relying solely on high-resolution spatial sampling, the system uses histogram-based probability distributions to represent depth measurements, effectively adding a statistical dimension that compensates for lower sensor resolution.
2Measurement precision
If conventional stereoscopic processing is used to improve depth map resolution, then depth map resolution is improved, but calculation time increases
Solution Approach 1:
The patent performs preliminary histogram computation and disparity range determination before full depth map processing. By pre-calculating disparity ranges based on time of flight measurements and histogram analysis, the system reduces the computational search space for subsequent stereoscopic matching, significantly reducing calculation time while maintaining depth map resolution.
Solution Approach 2:
The patent applies different processing strategies to different acquisition zones based on local characteristics. By analyzing histograms locally and adapting disparity search ranges to regional depth variations, the system optimizes calculation efficiency for each zone rather than applying uniform high-computation processing across the entire scene.
3Measurement precision
If conventional stereoscopic processing is used to improve depth map accuracy, then depth map accuracy is improved, but computational resource consumption increases
Solution Approach 1:
The system performs preliminary filtering and disparity range estimation using time of flight data and histograms before executing computationally intensive stereoscopic matching. This pre-processing step eliminates unnecessary computations by constraining the search space, reducing overall computational resource consumption while preserving depth map accuracy.
Solution Approach 2:
The patent uses time of flight measurements and histograms as intermediary data structures that guide and constrain the stereoscopic processing. These intermediaries provide rough depth estimates and disparity ranges that reduce the computational burden of precise stereoscopic matching, acting as a bridge between low-computation rough estimation and high-precision depth mapping.
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 an improved depth map resolution up to one thousand times greater than the time of flight sensor resolution, reduces calculation time, and adds additional depth information, while being compatible with lower-resolution, compact, and energy-efficient time of flight sensors, thus enhancing the reliability and efficiency of depth map determination.
Implementation Method 1
time of flight measurement consists in emitting onto a scene an identifiable electromagnetic wave signal, generally pulsed laser illumination, and detecting the signals reflected by the objects of the scene. The time difference between the moment of emission of a signal and the moment of reception of that signal reflected by an object of the scene enables calculation of the distance separating the transmitter-receiver from the object
Data Source
AI summary
The method of determination of a depth map of a scene comprises generation of a distance map of the scene obtained by time of flight measurements, acquisition of two images of the scene from two different viewpoints, and stereoscopic processing of the two images taking into account the distance map. The generation of the distance map includes generation of distance histograms acquisition zone by acquisition zone of the scene, and the stereoscopic processing includes, for each region of the depth map corresponding to an acquisition zone, elementary processing taking into account the corresponding histogram.