Ambiguous Depth Image Classification Using Environmental Models
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Solution Overview
Problem
Depth sensing systems face ambiguities in determining whether ambiguous image portions are 'dark' or 'far' due to insufficient photon detection, leading to visual inaccuracies and obscurities in applications like surface reconstruction.
Innovation Solution
Classifying ambiguous image portions by analyzing a model of the environment that represents depth and reflectivity values, comparing expected photon counts with calibrated values to distinguish between 'dark' and 'far' portions based on expected depth and reflectivity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If depth sensing systems mark dark portions and far portions as invalid in depth maps, then the system can handle ambiguous depth data, but visual inaccuracies and obscurities occur in applications like surface reconstruction
Solution Approach 1:
The patent segments ambiguous depth data into distinct categories (dark portions vs. far portions) by analyzing multiple factors including photon counts, depth values, and reflectivity. This segmentation allows each type of ambiguous data to be handled differently, preventing visual inaccuracies in surface reconstruction while maintaining reliable depth data validation.
2Ease of operation
If the system uses default logic to represent dark portions and far portions differently, then the system can process ambiguous data, but inconsistencies arise in visual representation
Solution Approach 1:
The patent applies local quality by using classification-specific representation logic for each type of ambiguous portion. Dark portions (objects with low reflectivity) are represented differently from far portions (areas beyond sensing range), with each classification receiving tailored processing appropriate to its physical meaning, thereby eliminating visual representation inconsistencies.
3Measurement precision
If the system requires a threshold number of photons to determine depth, then measurement reliability improves, but ambiguous portions of the image cannot be classified
Solution Approach 1:
The patent performs preliminary classification of ambiguous portions by analyzing available photon counts, depth values, and reflectivity data before final depth determination. This preliminary action allows the system to categorize ambiguous portions (identifying them as dark or far) even when photon counts fall below the threshold for precise depth measurement, thereby preventing information loss while maintaining measurement precision for sufficient data.
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
Improves the accuracy of depth sensing systems by effectively classifying ambiguous image data, reducing visual inaccuracies and enhancing the functionality of depth data applications.
Implementation Method 1
some depth sensing systems (i.e., Time-of-Flight (ToF) camera systems) project light onto a real world environment and resolve depth based on the known speed of light and the round trip time-of-flight of light signals
Implementation Method 2
one or more light projecting sensors to project light (i.e., infrared light, near-infrared light, etc.) onto an environment and capture the reflected light signals which bounce off objects in the environment
Data Source
AI summary
Ambiguous portions of an image which have fewer photons of a reflected light signal detected than required to determine depth can be classified as being dark (i.e., reflecting too few photons to derive depth) and/or far (i.e., beyond a range of a camera) based at least in part on expected depth and reflectivity values. Expected depth and reflectivity values for the ambiguous portions of the image may be determined by analyzing a model of an environment created by previously obtained images and depth and reflectivity values. The expected depth and reflectivity values may be compared to calibrated values for a depth sensing system to classify the ambiguous portions of the image as either dark or far based on the actual photon count detected for the image.