Open Access. Powered by Scholars. Published by Universities.®

Engineering Commons

Open Access. Powered by Scholars. Published by Universities.®

2008

University of Central Florida

Computer vision

Articles 1 - 2 of 2

Full-Text Articles in Engineering

Multi-View Approaches To Tracking, 3d Reconstruction And Object Class Detection, Saad Khan Jan 2008

Multi-View Approaches To Tracking, 3d Reconstruction And Object Class Detection, Saad Khan

Electronic Theses and Dissertations

Multi-camera systems are becoming ubiquitous and have found application in a variety of domains including surveillance, immersive visualization, sports entertainment and movie special effects amongst others. From a computer vision perspective, the challenging task is how to most efficiently fuse information from multiple views in the absence of detailed calibration information and a minimum of human intervention. This thesis presents a new approach to fuse foreground likelihood information from multiple views onto a reference view without explicit processing in 3D space, thereby circumventing the need for complete calibration. Our approach uses a homographic occupancy constraint (HOC), which states that if …


Detecting Curved Objects Against Cluttered Backgrounds, Jan Prokaj Jan 2008

Detecting Curved Objects Against Cluttered Backgrounds, Jan Prokaj

Electronic Theses and Dissertations

Detecting curved objects against cluttered backgrounds is a hard problem in computer vision. We present new low-level and mid-level features to function in these environments. The low-level features are fast to compute, because they employ an integral image approach, which makes them especially useful in real-time applications. The mid-level features are built from low-level features, and are optimized for curved object detection. The usefulness of these features is tested by designing an object detection algorithm using these features. Object detection is accomplished by transforming the mid-level features into weak classifiers, which then produce a strong classifier using AdaBoost. The resulting …