Title

SURF Tracking of Occluded Objects

Document Type

Thesis

Degree Name

Master of Science (MS)

Department

Computer Science and Info Sys

Date of Award

Spring 2016

Abstract

For a large class of applications, which includes human-computer interaction, security, surveillance and traffic control, detection and tracking targets are an essential step in understanding the motion of objects. Target tracking becomes more challenging and complex as the scene starts to include more real world objects. In this study we present a method to capture and track moving objects using Speeded Up Robust Features (SURF) features. The target is user specified. SURF features are extracted from the target and are matched to the SURF features in the image frame taken from the video. When a match is found the target is boxed to show its location. The process is continued for all the frames of the video. Occlusion is taken into consideration and the algorithm successfully tracks both partially and completely occluded objects. This approach is applied to both synthetically developed and real life videos to capture different kinds of targets in different scenarios. Concepts were validated in a MATLAB environment and the experimental results are documented.

Advisor

Nikolay M. Sirakov

Subject Categories

Computer Sciences | Physical Sciences and Mathematics

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