Heterogeneous Stereo Camera Pair for Vehicle Depth Estimation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional stereo vision systems in automotive applications are limited by the use of identical cameras with parallel optical axes, which restricts their practicality and computational complexity, making them unsuitable for real-world applications.
Innovation Solution
A heterogeneous vehicle camera stereo pair system that utilizes different cameras with arbitrarily placed and oriented optical axes, allowing for overlapping fields of view, such as a fisheye camera and a pinhole camera, to provide depth estimation for driver assist and autonomous driving systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If identical cameras with parallel optical axes are used, then computational complexity is reduced and software is simplified, but adaptability to real-world automotive applications is limited
Solution Approach 1:
The patent applies asymmetry by using heterogeneous camera types (e.g., fisheye and pinhole cameras) with different optical characteristics instead of identical cameras. This asymmetric configuration allows the system to adapt to various automotive mounting positions and orientations while maintaining depth estimation capability, thereby improving adaptability without significantly increasing computational complexity through specialized processing pipelines
Solution Approach 2:
The patent implements dynamics by allowing cameras to be positioned and oriented in arbitrary configurations rather than fixed parallel arrangements. The system dynamically adapts to different camera placements (vertical, horizontal, angled) and orientations by adjusting the stereo vision processing accordingly, enabling versatility in real-world automotive installations while managing computational load through adaptive algorithms
2Device complexity
If cameras are placed horizontally with parallel optical axes, then the search space for matching points is limited and software is simplified, but practicality in real-world automotive applications is reduced
Solution Approach 1:
The patent applies universality by creating a stereo vision system that can handle multiple camera configurations (horizontal, vertical, angled placements) and camera types (fisheye, pinhole, and other lenses) through a unified processing framework. This universal approach allows the same software to manage diverse automotive camera installations without requiring configuration-specific code paths, thereby maintaining software simplicity while improving practicality
Solution Approach 2:
The patent implements parameter changes by allowing variation in camera positioning parameters (vertical offset, horizontal offset, angular orientation) and optical parameters (focal length, field of view) while maintaining consistent depth estimation functionality. The system adapts to different parameter configurations through calibration and processing adjustments, enabling practical automotive deployment without proportionally increasing software complexity
3Device complexity
If conventional stereo pair constraints are applied, then computational complexity is minimized, but the system cannot effectively utilize dissimilar camera types and arbitrary placements
Solution Approach 1:
The patent introduces an intermediary calibration and processing layer that mediates between heterogeneous camera inputs and the depth estimation algorithm. This intermediary component handles the transformation and normalization of images from dissimilar camera types (fisheye, pinhole) and arbitrary placements into a unified representation that can be processed with adapted versions of standard stereo algorithms, thereby enabling camera diversity without prohibitively increasing computational complexity
Solution Approach 2:
The patent applies preliminary action through pre-calibration procedures that establish transformation models and disparity mappings for specific camera pairs before actual depth estimation. By performing preliminary characterization of each camera's optical properties and geometric relationship during installation, the system prepares lookup tables and parameter sets that reduce real-time computational burden, enabling support for dissimilar camera types while keeping operational complexity manageable
Data Source
AI summary
A stereo pair camera system for depth estimation, including: a first camera disposed in a first position along a longitudinal axis, a lateral axis, and a vertical axis and having a first field of view; and a second camera disposed in a second position along the longitudinal axis, the lateral axis, and the vertical axis and having a second field of view; wherein the first camera is a of a first type and the second camera is of a second type that is different from the first type; and wherein the first field of view overlaps with the second field of view. Optionally, the first position is spaced apart from the second position along one or more of the longitudinal axis and the vertical axis. The depth estimation is used by one or more of a driver assist system and an autonomous driving system of a vehicle.