This paper describes a machine learning approach for visual
object detection which is capable of processing images
extremely rapidly and achieving high detection rates. This
wor...
For applications such as video surveillance and human computer interface, we propose an efficiently integrated method to detect and track faces. Various visual cues are combined t...
Tae-Kyun Kim, Sung-Uk Lee, Jong Ha Lee, Seok-Cheol...
This paper presents a novel face detection method in video by using Discriminating Feature Analysis (DFA) and Support Vector Machine (SVM). Our method first incorporates temporal ...
Although not commonly used, correlation filters can track complex objects through rotations, occlusions and other distractions at over 20 times the rate of current state-ofthe-ar...
David Bolme, J Ross Beveridge, Bruce Draper, Yui M...
We propose a high performance architecture for fractional motion estimation and Lagrange mode decision in H.264/AVC. Instead of time-consuming fractional-pixel interpolation and s...