Salient object detection, which simulates human visual perception in locating the most
significant object (s) in a scene, has been widely applied to various computer vision tasks …

Human activity recognition is an important area of computer vision research. Its applications
include surveillance systems, patient monitoring systems, and a variety of systems that …

RGB-D saliency detection has attracted increasing attention, due to its effectiveness and the
fact that depth cues can now be conveniently captured. Existing works often focus on …

Vision-based human action recognition is the process of labeling image sequences with
action labels. Robust solutions to this problem have applications in domains such as visual …

Detecting and segmenting salient objects from natural scenes, often referred to as salient
object detection, has attracted great interest in computer vision. While many models have …

Understanding and predicting the human visual attention mechanism is an active area of
research in the fields of neuroscience and computer vision. In this paper, we propose …

The paper introduces Hough forests, which are random forests adapted to perform a
generalized Hough transform in an efficient way. Compared to previous Hough-based …

Human Action Recognition (HAR) is the classification of an action performed by a human.
The goal of this study was to recognize human actions in action video sequences. We …

Slow Feature Analysis (SFA) extracts slowly varying features from a quickly varying input
signal [1]. It has been successfully applied to modeling the visual receptive fields of the …

Multimodal streams of sensory information are naturally parsed and integrated by humans
using signal-level feature extraction and higher level cognitive processes. Detection of …