Date of Award
Master of Science
Electrical and Computer Engr
Lavonnie Perry Claybon
Peter S Lau
A system capable of detection and localization of objects of interest in a semi-structured environment will enhance the quality of life of people who are blind or visually impaired. Towards building such a system, this thesis presents a personalized real-time system called O'Map that finds misplaced/moved personal items and localizes them with respect to known landmarks. First, we adopted a participatory design approach to identify users’ need and functionalities of the system. Second, we used the concept from system thinking and design thinking to develop a real-time object recognition engine that was optimized to run on low form factor devices. The object recognition engine finds robust correspondences between the query image and item templates using K-D tree of invariant feature descriptor with two nearest neighbors and ratio test. Quantitative evaluation demonstrates that O'Map identifies object of interest with an average F-measure of 0.9650.
dissertation or thesis originally submitted to the local University of Memphis Electronic Theses & dissertation (ETD) Repository.
Alam, Shahinur, "OMap: An assistive solution for identifying and localizing objects in a semi-structured environment" (2016). Electronic Theses and Dissertations. 1342.