: Dimensionality reduction methods (DRs) have commonly been used as a principled way to understand the high-dimensional data such as face images. In this paper, we propose a new un...
Local invariant feature based methods have been proven to be effective in computer vision for object recognition and learning. But for an image, the number of points detected and ...
We present a novel algorithm, Compact Kd-Trees (CompactKdt), that achieves state-of-the-art performance in searching large scale object image collections. The algorithm uses an or...
Local space-time features have recently shown promising results within Bag-of-Features (BoF) approach to action recognition in video. Pure local features and descriptors, however,...
Muhammad Muneeb Ullah, Sobhan Naderi Parizi, Ivan ...
A new feature descriptor is presented for object and scene recognition. The new approach, called CDIKP, uniquely combines the scale-invariant feature detection with a robust proje...