Iris-Based Monocular Depth Estimation for Facial Image Enhancement
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Solution Overview
Problem
Existing image capture devices, such as stereo cameras, require multiple components to generate depth information, increasing costs and complexity.
Innovation Solution
A single image capturing component, like a smartphone, identifies a person's face, generates a facial mesh, estimates eye pixel dimensions, and uses the intrinsic matrix to calculate depth, enabling depth estimation without multiple cameras.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a stereo camera set up is used to generate 3D information, then depth information can be obtained, but the costs and complexity increase due to multiple image capture components
Solution Approach 1:
The patent extracts the depth estimation function from the complex stereo camera system and implements it using a single image capture component. By using facial mesh analysis and eye landmark detection on monocular images, the system obtains depth information without requiring multiple cameras, thus reducing device complexity while maintaining measurement precision for depth.
Solution Approach 2:
The patent replaces the mechanical stereo camera system with a computational approach using a single camera. Instead of using multiple physical image capture components to capture simultaneous images for depth calculation, the system uses image processing algorithms that analyze facial geometry and eye landmarks to estimate depth, substituting mechanical complexity with computational methods.
2Measurement precision
If multiple image capture components are used to create 3D stereoscopic image, then depth information is generated, but the cost increases
Solution Approach 1:
The patent extracts the essential depth estimation capability from the expensive stereo camera system and implements it using a single, more affordable image capture component. By using software-based facial mesh analysis and eye landmark detection, the system achieves depth information at lower cost, making the technology more accessible while maintaining measurement precision.
3Device complexity
If a single image capturing component is used, then cost and complexity are reduced, but depth estimation capability must be achieved through alternative methods
Solution Approach 1:
The patent introduces an intermediary computational model - the facial mesh with eye landmarks - that mediates between the single image capture component and the depth estimation goal. This intermediary framework allows the system to extract depth information from 2D images by analyzing geometric relationships in the facial mesh, making depth measurement feasible with minimal hardware.
Solution Approach 2:
The patent changes the parameters used for depth estimation from traditional stereo vision methods to facial geometry-based parameters. By analyzing eye landmark positions, iris pixel dimensions, and facial mesh characteristics, the system estimates depth using different measurement parameters that are derivable from single images, thus overcoming the limitations of monocular imaging.
Data Source
AI summary
Example embodiments relate to estimating depth information based on iris size. A computing system may obtain an image depicting a person and determine a facial mesh for a face of the person based on features of the face. In some instances, the facial mesh includes a combination of facial landmarks and eye landmarks. As such, the computing system may estimate an iris pixel dimension of an eye based on the eye landmarks of the facial mesh and estimate a distance of the eye of the face relative to the camera based on the iris pixel dimension, a mean value iris dimension, and an intrinsic matrix of the camera. The computing system may further modify the image based on the estimated distance.