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Depth Not Needed - An Evaluation of RGB-D Feature Encodings for Off-Road Scene Understanding by Convolutional Neural Network
Scene understanding for autonomous vehicles is a challenging computer vi...
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A Machine Learning Approach to Recovery of Scene Geometry from Images
Recovering the 3D structure of the scene from images yields useful infor...
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A Complete System for Candidate Polyps Detection in Virtual Colonoscopy
Computer tomographic colonography, combined with computer-aided detectio...
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Multiple Lane Detection Algorithm Based on Optimised Dense Disparity Map Estimation
Lane detection is very important for self-driving vehicles. In recent ye...
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Disp R-CNN: Stereo 3D Object Detection via Shape Prior Guided Instance Disparity Estimation
In this paper, we propose a novel system named Disp R-CNN for 3D object ...
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GroundNet: Segmentation-Aware Monocular Ground Plane Estimation with Geometric Consistency
We focus on the problem of estimating the orientation of the ground plan...
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Low-level Vision by Consensus in a Spatial Hierarchy of Regions
We introduce a multi-scale framework for low-level vision, where the goa...
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Non-flat Road Detection Based on A Local Descriptor
The detection of road and free space remains challenging for non-flat plane, especially with the varying latitudinal and longitudinal slope or in the case of multi-ground plane. In this paper, we propose a framework of the ground plane detection with stereo vision. The main contribution of this paper is a newly proposed descriptor which is implemented in the disparity image to obtain a disparity texture image. The ground plane regions can be distinguished from their surroundings effectively in the disparity texture image. Because the descriptor is implemented in the local area of the image, it can address well the problem of non-flat plane. And we also present a complete framework to detect the ground plane regions base on the disparity texture image with convolutional neural network architecture.
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