An Automated Object Detection and Tracking through Multi-Modal Image Fusion

This research project will develop an automated maritime object detection and tracking system using fused images from infrared and visible RGB sources. The developed system can be deployed and used in patrol vessels for maritime surveillance. As the system takes advantage of both infrared and visible RGB images, it is capable of running for 24 hours all over the year under various illumination and different weather conditions. By efficiently and effectively detecting and tracking maritime objects, the system will provide timely and accurate information about maritime objects. The partner organization can take this system as the maritime surveillance software solution and attract more investments and collaborations. Overall, the developed system will enhance the maritime surveillance software system and benefit Canadian ocean safety.

Faculty Supervisor:

Zheng Liu

Student:

Partner:

TerraSense Analytics Ltd

Discipline:

Engineering

Sector:

Agriculture; Professional, scientific and technical services

University:

The University of British Columbia - Okanagan

Program: