Recognizing and localizing objects is a classical problem in computer vision that is an important stage for many automated systems. In order to perform object recognition many res...
A richer set of land-cover classes are observable in satellite imagery than ever before due to the increased sub-meter resolution. Individual objects, such as cars and houses, are...
This paper presents a unified framework for 3D shape retrieval. The method supports multimodal queries (2D images, sketches, 3D objects) by introducing a novel view-based approach...
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...
PCA-SIFT is an extension to SIFT which aims to reduce SIFT’s high dimensionality (128 dimensions) by applying PCA to the gradient image patches. However PCA is not a discriminati...