Multi-Camera Depth Estimation Using Semantic Transfer
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Solution Overview
Problem
Multi-camera systems with large focal lengths struggle to achieve sufficient overlap between views for depth estimation of distant objects, leading to low resolution and unreliable depth estimation, while systems with short focal lengths lack sufficient overlap for accurate depth estimation of nearby objects.
Innovation Solution
A method involving two sets of cameras with different focal lengths, where one set generates semantic information that is processed to improve the depth estimation accuracy of the other set, utilizing techniques such as segmentation, background geometry modeling, and calibration to enhance depth maps.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If a multi-camera system uses a large focal length to capture distant objects at high resolution, then the imaging resolution of distant objects is improved, but the overlap between views becomes insufficient for depth estimation
Solution Approach 1:
The patent segments the camera system into two distinct sets: a first set of cameras with shorter focal lengths optimized for depth estimation, and a second set of cameras with longer focal lengths optimized for high-resolution imaging of distant objects. This segmentation allows each subset to perform its specialized function without compromise.
Solution Approach 2:
The patent introduces semantic information as an intermediary that bridges the two camera sets. The semantic information, generated from the first set of images, serves as a mediator to enhance the second set of images, transferring depth estimation capabilities to the long-focal-length camera system.
2Reliability
If a multi-camera system uses a short focal length to achieve sufficient overlap between views, then the depth estimation reliability is improved, but the imaging resolution of distant objects deteriorates
Solution Approach 1:
The patent divides the imaging system into specialized subsets: short-focal-length cameras for depth estimation and long-focal-length cameras for high-resolution imaging, allowing each to optimize for its specific function without compromise.
Solution Approach 2:
Semantic information acts as an intermediary that transfers the depth estimation advantages of the short-focal-length camera system to the long-focal-length camera system, enabling the latter to produce high-resolution images with accurate depth information.
3Device complexity
If a single focal length is used for all cameras, then the system complexity is reduced, but the ability to capture both distant and nearby objects with optimal quality is compromised
Solution Approach 1:
The patent creates a universal camera system where two different focal length configurations work together synergistically. The system achieves multi-functionality by combining the depth estimation capability of short-focal-length cameras with the high-resolution distant object capture capability of long-focal-length cameras, with semantic information bridging their functions.
Data Source
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AI summary
A system and method for depth estimation. 2D images are acquired by cameras that are divided into at least two sets according to focal length. Images acquired by one of the sets of cameras are processed to generate semantic information, which is in turn processed to generate a depth map for each image acquired by another set of cameras.