Real-time detection and tracking of text in videos

Majid Mirmehdi

(University of Bristol)

We present a real-time text tracking system capable of detecting and tracking text using a hand-held mobile camera at rates of above 25 frames per second. The method is based on extracting text regions using a novel tree-based connected component filtering approach, combined with the Eigen-Transform texture descriptor. The method can efficiently handle dark and light text on light and dark backgrounds. Predictive tracking (using either particle filters or the unscented Kalman Filter) is used to follow the text in the face of multiple regions of interest, fast displacements, and erratic motions. Strengths and shortcomings of the approach, plus future work, will be discussed.
Thursday 19th February 2009, 14:00
Robert Recorde Room
Department of Computer Science