Human activity recognition (HAR) is an important research area in the fields of human
perception and computer vision due to its wide range of applications. These applications …

We address the task of jointly determining what a person is doing and where they are
looking based on the analysis of video captured by a headworn camera. We propose a …

We introduce an unsupervised, geodesic distance based, salient video object segmentation
method. Unlike traditional methods, our method incorporates saliency as prior for object via …

Recently dense trajectories were shown to be an efficient video representation for action
recognition and achieved state-of-the-art results on a variety of datasets. This paper …

We address the problem of action detection in videos. Driven by the latest progress in object
detection from 2D images, we build action models using rich feature hierarchies derived …

Visual saliency analysis detects salient regions/objects that attract human attention in
natural scenes. It has attracted intensive research in different fields such as computer vision …

A novel Boolean Map based Saliency (BMS) model is proposed. An image is characterized
by a set of binary images, which are generated by randomly thresholding the image's color …

Research in visual saliency has been focused on two major types of models namely fixation
prediction and salient object detection. The relationship between the two, however, has …

We address the challenging problem of recognizing the camera wearer's actions from
videos captured by an egocentric camera. Egocentric videos encode a rich set of signals …

This paper introduces a state-of-the-art video representation and applies it to efficient action
recognition and detection. We first propose to improve the popular dense trajectory features …