DSD: Depth Structural Descriptor for Edge-Based Assistive Navigation
Date
2017
Authors
Feng, David
Barnes, Nick
You, Shaodi
Journal Title
Journal ISSN
Volume Title
Publisher
IEEE
Abstract
Structural edge detection is the task of finding edges between significant surfaces in a scene. This can underpin many computer vision tasks such as sketch recognition and 3D scene understanding, and is important for conveying scene structure for navigation with assistive vision. Identifying structural edges from a depth image can be challenging because surface structure that differentiates edges is not well represented in this format. We derive a depth input encoding, the Depth Surface Descriptor (DSD), that captures the first order properties of surfaces, allowing for improved classification of surface geometry that corresponds to structural edges. We apply the DSD feature to salient edge detection on RGB-D images using a fully convolutional neural network with deep supervision. We evaluate our method on both a new RGB-D dataset containing prosthetic vision scenarios, and the SUNRGBD dataset, and show that our approach produces improved performance compared to existing methods by 4%.
Description
Keywords
Citation
Collections
Source
Proceedings - 2017 IEEE International Conference on Computer Vision Workshops, ICCVW 2017
Type
Conference paper
Book Title
Entity type
Access Statement
License Rights
Restricted until
2099-12-31