Vision-Based Human Directed Robot Guidance

This paper describes methods to track a user-defined point in the vision of a robot as it drives forward. This tracking allows a robot to keep itself directed at that point while driving so that it can get to that user-defined point. I develop and present two new multi-scale algorithms for tracking arbitrary points between two frames of video, as well as through a video sequence. The multi-scale algorithms do not use the traditional pyramid image, but instead use a data structure called an integral image (also known as a summed area table). The first algorithm uses edge-detection to track the movement of the tracking point between frames of video. The second algorithm uses a modified version of the Moravec operator to track the movement of the tracking point between frames of video. Both of these algorithms can track the user-specified point very quickly. Implemented on a conventional desktop, tracking can proceed at a rate of at least 20 frames per second.

Name thesis:degree_name

MS

Grantor dc:publisher

Brigham Young University - Provo

Author dc:creator

• Arthur, Richard B.

• computer
• machine vision
• machine learning
• video
• point tracking
• visual servoing
• integral image
• summed area table
• minimal edit distance
• Moravec operator
• Computer Sciences

Language dc:language

English

Repository record dc:identifier

https://scholarsarchive.byu.edu/etd/190

OAI identifier oai:identifier

oai:scholarsarchive.byu.edu:etd-1189