Reliable facial expression recognition by machine is still a challenging task. We propose a framework to recognise various expressions by tracking facial features. Our method uses...
We present an algorithm that learns invariant features from real data in an entirely unsupervised fashion. The principal benefit of our method is that it can be applied without hu...
Object detection remains an important but challenging task in computer vision. We present a method that combines high accuracy with high efficiency. We adopt simplified forms of...
We consider the problem of learning classifiers in structured domains, where some objects have a subset of features that are inherently absent due to complex relationships between...
Gal Chechik, Geremy Heitz, Gal Elidan, Pieter Abbe...
The focus of this work is on the problem of feature selection and classification for on-road vehicle detection. In particular, we propose using quantized Haar wavelet features an...