We propose a novel approach based on deep Convolutional Neural Networks (CNN) to
recognize human actions in still images by predicting the future motion, and detecting the …

Most multispectral remote sensors (eg QuickBird, IKONOS, and Landsat 7 ETM+) provide
low-spatial high-spectral resolution multispectral (MS) or high-spatial low-spectral resolution …

Image search and retrieval engines rely heavily on textual annotation in order to match word
queries to a set of candidate images. A system that can automatically annotate images with …

Multiview super-resolution image reconstruction (SRIR) is often cast as a resampling
problem by merging non-redundant data from multiple low-resolution (LR) images on a finer …

Automatic annotation of images with descriptive words is a challenging problem with vast
applications in the areas of image search and retrieval. This problem can be viewed as a …

We propose a novel motion estimation/compensation (ME/MC) method for wavelet-based (in-
band) motion compensated temporal filtering (MCTF), with application to low-bitrate video …

Introduction. Semantic annotation is the process of attaching additional information to
various concepts (eg people, things, places, organizations etc) in a given text or any other …

Self-similarity was recently introduced as a measure of inter-class congruence for
classification of actions. Herein, we investigate the dual problem of intra-class dissimilarity …

In this paper, we show that different body parts do not play equally important roles in
recognizing a human action in video data. We investigate to what extent a body part plays a …

This paper focuses on real-time all-frequency image-based rendering using an innovative
solution for run-time computation of light transport. The approach is based on new results …