IntelliNavi : Navigation for blind based on kinect and machine learning

被引：17

作者：

Bhowmick, Alexy ^{[1
]}

Prakash, Saurabh ^{[1
]}

Bhagat, Rukmani ^{[1
]}

Prasad, Vijay ^{[1
]}

Hazarika, Shyamanta M. ^{[2
]}

机构：

[1] School of Technology, Assam Don Bosco University, Guwahati, Assam

[2] School of Engineering, Tezpur University, Tezpur, Assam

来源：

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | 2014年 / 8875卷

关键词：

Blind; Kinect; Machine learning; Navigation systems; Object recognition; RGB-D;

D O I：

10.1007/978-3-319-13365-2_16

中图分类号：

学科分类号：

摘要：

This paper presents a wearable navigation assistive system for the blind and the visually impaired built with off-the-shelf technology. Microsoft Kinect’s on board depth sensor is used to extract Red, Green, Blue and Depth (RGB-D) data of the indoor environment. Speeded-Up Robust Features (SURF) and Bag-of-Visual-Words (BOVW) model is used to extract features and reduce generic indoor object detection into a machine learning problem. A Support Vector Machine classifier is used to classify scene objects and obstacles to issue critical real-time information to the user through an external aid (earphone) for safe navigation. We performed a user-study with blind-fold users to measure the efficiency of the overall framework. ©Springer International Publishing Switzerland 2014.

引用

页码：172 / 183

页数：11

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