Colloquia Speaker, Maha El Choubassi, Intel, "Intensity-Based Camera Pose Estimation in Presence of Depth"
The widespread success of Kinect enables users to acquire both image and depth information with satisfying accuracy at relatively low cost. We leverage the Kinect output to efficiently and accurately estimate the camera pose in presence of rotation, translation, or both.
The applications of our algorithm are vast ranging from camera tracking, to 3D points clouds registration, and video stabilization. The state-of-the-art approach uses point correspondences for estimating the pose. More explicitly, it extracts point features from images, e.g., SURF or SIFT, and builds their descriptors, and matches features from different images to obtain point correspondences. However, while features-based approaches are widely used, they perform poorly in scenes lacking texture due to scarcity of features or in scenes with repetitive structure due to false correspondences. Our algorithm is intensity-based and requires neither point features' extraction, nor descriptors' generation /matching. Due to absence of depth, the intensity-based approach alone cannot handle camera translation. With Kinect capturing both image and depth frames, we extend the intensity-based algorithm to estimate the camera pose in case of both 3D rotation and translation.
Maha El Choubassi got her MSc and PhD in electrical engineering from University of Illinois at Urbana-Champaign in 2005 and 2008 respectively. Her areas of interests are signal/image processing, computer vision, pattern recognition, and watermarking. Maha has rejoined the image processing and computer vision group at Intel In September 2013. Earlier, she was an Intel research scientist from February 2009 to March 2011. After working at Intel, Maha joined the computer science department at the American University of Beirut (AUB) for the last two years. In her academic job, Maha taught various courses on computer architecture, image processing, and pattern recognition. Additionally, she has worked with graduate students and colleagues on image processing and computer vision research projects.
Friday, February 14, 2014 at 12:00pm to 1:00pm
Davidson Math and Science Center, 102
1055 Evans Avenue, Reno, NV 89512, USA