An Obstacle Avoidance System for Visual Impaired People Based on Object Tracking Algorithm and Semantic Segmentation

Xianghao Meng, Wei Shi, Rui Shan, Yoshihiro Okada

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Many visually impaired people face safety issues when walking outside. Providing a safe method to guide such individuals in complex road situations is a widely discussed challenge. With the advancement of deep learning, we have proposed an obstacle avoidance system to address this problem. In this system, a 360-degree camera is used as an input device to record the surrounding environment of users. Deep learning technologies, specifically ByteTrack and MMSegmentation, are employed to process the video data. As a result, the system provides multi-modal feedback to users, helping them avoid obstacles.

Original languageEnglish
Title of host publication2024 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798331530839
DOIs
Publication statusPublished - 2024
Event2024 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2024 - Danang, Viet Nam
Duration: Nov 3 2024Nov 6 2024

Publication series

Name2024 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2024

Conference

Conference2024 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2024
Country/TerritoryViet Nam
CityDanang
Period11/3/2411/6/24

All Science Journal Classification (ASJC) codes

  • Human-Computer Interaction
  • Electrical and Electronic Engineering
  • Media Technology
  • Modelling and Simulation
  • Instrumentation

Fingerprint

Dive into the research topics of 'An Obstacle Avoidance System for Visual Impaired People Based on Object Tracking Algorithm and Semantic Segmentation'. Together they form a unique fingerprint.

Cite this