Monocular Free Space Estimation via Dynamic Programming
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for free space estimation in autonomous navigation, particularly for vehicles and boats, face challenges when using monocular cameras due to issues like reflection and non-flat surfaces, which complicates the segmentation of water and road features, and lack effective solutions for maritime scenes.
Innovation Solution
A method using dynamic programming to segment free space from monocular video sequences by formulating the problem as an optimization in a Markov random field, incorporating features like appearance, edges, homographies, and smoothness, and employing structured support vector machines to determine weight parameters for energy functions, allowing for reliable free space estimation without relying on stereoscopic or 3D sensors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If stereo cameras are used for free space estimation, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent uses a monocular camera to capture images that copy the visual scene, then applies computer vision algorithms to extract depth and free space information from these 2D images, effectively replacing the need for stereo camera systems while maintaining measurement capability
Solution Approach 2:
The patent replaces the mechanical stereo vision system with a computational approach using monocular images and algorithms including dynamic programming, homography estimation, and energy minimization to achieve free space measurement
2Device complexity
If monocular camera is used to reduce system complexity, then device complexity is reduced, but measurement precision deteriorates due to reflection and non-flat surfaces
Solution Approach 1:
The patent changes the parameter representation by formulating free space estimation as an energy minimization problem with multiple terms (data fidelity, smoothness, homography consistency) that can handle varying conditions including reflections and non-flat surfaces
Solution Approach 2:
The patent introduces homography estimation as an intermediary step that models the transformation between camera views, serving as a mediator to disambiguate between actual scene geometry and artifacts like reflections or water surface variations
3Manufacturing precision
If dynamic programming is used for segmentation, then manufacturing precision is improved, but loss of time increases due to computational optimization
Solution Approach 1:
The patent applies dynamic programming selectively to specific regions or aspects of the image processing pipeline, and uses approximate or greedy variants where full optimization would be too costly, balancing precision and computation time
Data Source
AI summary
A method estimates free space near a moving object from a sequence of images in a video acquired of a scene by a camera system arranged on the moving object by first constructing a one-dimensional graph, wherein each node corresponds to a column of pixels in the image. Features are determined in the image, and an energy function is constructed on the graph based on the features. Using dynamic programming, the energy function is maximized to obtain the free space.