Fusion of non-visual and visual sensors for human tracking

"Human tracking is an extensively researched yet still challenging area in the Computer Vision field, with a wide range of applications such as surveillance and healthcare. People may not be successfully tracked with merely the visual information in challenging cases such as long-term occlusion. Thus, we propose to combine information from other sensors with the surveillance cameras to persistently localize and track humans, which is becoming more promising with the pervasiveness of mobile devices such as cellphones, smart watches and smart glasses embedded with all kinds of sensors including accelerometers, gyroscopes, magnetometers, GPS, WiFi modules and so on. In this thesis, we firstly investigate the application of Inertial Measurement Unit (IMU) from mobile devices to human activity recognition and human tracking, we then develop novel persistent human tracking and indoor localization algorithms by the fusion of non-visual sensors and visual sensors, which not only overcomes the occlusion challenge in visual tracking, but also alleviates the calibration and drift problems in IMU tracking"--Abstract, page iii.

Name thesis:degree_name

Ph. D. in Computer Science

Grantor

Missouri University of Science and Technology

Author dc:creator

• Jiang, Wenchao

• Activity Recognition
• Human Tracking
• Information Fusion
• Computer Sciences

Repository record dc:identifier

https://scholarsmine.mst.edu/doctoral_dissertations/2562

OAI identifier oai:identifier

oai:scholarsmine.mst.edu:doctoral_dissertations-3567