Real-time Object Detection using Deep Learning for helping People with Visual Impairments

Terreran, Matteo, Tramontano, Andrea, Lock, Jacobus , Ghidoni, Stefano and Bellotto, Nicola (2020) Real-time Object Detection using Deep Learning for helping People with Visual Impairments. In: 4th IEEE International Conference on Image Processing, Applications and Systems (IPAS), 9-11 Dec 2020, Genova, Italy.

Documents
Real-time Object Detection using Deep Learning for helping People with Visual Impairments
Authors' Accepted Manuscript

Request a copy
[img] PDF
42338.pdf - Whole Document
Restricted to Repository staff only until 9 December 2021.

2MB
Item Type:Conference or Workshop contribution (Paper)
Item Status:Live Archive

Abstract

Object detection plays a crucial role in the development of Electronic Travel Aids (ETAs), capable to guide a person with visual impairments towards a target object in an unknown indoor environment. In such a scenario, the object detector runs on a mobile device (e.g. smartphone) and needs to be fast, accurate, and, most importantly, lightweight. Nowadays, Deep Neural Networks (DNN) have become the state-of-the-art solution for object detection tasks, with many works improving speed and accuracy by proposing new architectures or extending existing ones. A common strategy is to use deeper networks to get higher performance, but that leads to a higher computational cost which makes it impractical to integrate them on mobile devices with limited computational power. In this work we compare different object detectors to find a suitable candidate to be implemented on ETAs, focusing on lightweight models capable of working in real-time on mobile devices with a good accuracy. In particular, we select two models: SSD Lite with Mobilenet V2 and Tiny-DSOD. Both models have been tested on the popular OpenImage dataset and a new dataset, called Office dataset, collected to further test models’ performance and robustness in a real scenario inspired by the actual perception challenges of a user with visual impairments.

Keywords:Object detection, real-time, vision impairment
Subjects:G Mathematical and Computer Sciences > G700 Artificial Intelligence
G Mathematical and Computer Sciences > G440 Human-computer Interaction
G Mathematical and Computer Sciences > G740 Computer Vision
Divisions:College of Science > School of Computer Science
Related URLs:
ID Code:42338
Deposited On:14 Dec 2020 10:23

Repository Staff Only: item control page