This paper describes a user detection system which employs a saliency system delivering a rough and fast estimate of the position of a potential user. This saliency system consists of a vision (skin color) and a sonar based component, which are combined to make the estimate more reliable. To make the skin color detection robust under varying illumination conditions, it is supplied with an autom...

Saliency detection is a long standing problem in computer vision. Tremendous efforts have been focused on exploring a universal saliency model across users despite their differences in gender, race, age, etc. Yet recent psychology studies suggest that saliency is highly specific than universal: individuals exhibit heterogeneous gaze patterns when viewing an identical scene containing multiple s...

In this paper, we will investigate the contribution of color names for salient object detection. Each input image is first converted to the color name space, which is consisted of 11 probabilistic channels. By exploring the topological structure relationship between the figure and the ground, we obtain a saliency map through a linear combination of a set of sequential attention maps. To overcom...

Online tracking has shown to be successful in tracking of previously unknown objects. However, there are two important factors which lead to drift problem of online tracking, the one is how to select the exact labeled samples even when the target locations are inaccurate, and the other is how to handle the confusors which have similar features with the target. In this article, we propose a robu...

Saliency detection means detecting visually attractive regions in images. It is an aspect of exploring visual attention from a computer vision. Each image is segmented to get bags. Features are extracted from each bag. Features, including low-, mid-,and high-level, are incorporated into the learning and testing process. They are position, color, texture, scale, center prior, and boundary. From ...

Visual saliency detection has been of great research interest in recent years, since it is potential for a wide range of applications, such as object detection, content-based image retrieval and perceptual image compression. Human perceptual attention usually tends to firstly pick attended regions, which correspond to prominent objects in an image, rather than the whole image (Jams, 1890; Itti,...

This article proposes a novel framework for the recognition of six universal facial expressions. The framework is based on three set of features extracted from the face image: entropy, brightness and local binary pattern. First, saliency maps are obtained by state-of-the-art saliency detection algorithm i.e. “frequency-tuned salient region detection”. The idea is to use saliency maps to find ap...

Visual saliency computation is about detecting and understanding salient regions and elements in a visual scene. Algorithms for visual saliency computation can give clues to where people will look in images, what objects are visually prominent in a scene, etc. Such algorithms could be useful in a wide range of applications in computer vision and graphics. In this thesis, we study the following ...

Recently there has been remarkable success in pushing the state of the art in salient object detection. Most of the improvements are driven by employing end-to-end deeper feed-forward networks. However, in many cases precisely detecting salient regions requires representation of fine details. Combining high-level and low-level features using skip connections is a strategy that has been proposed...

Detection of moving foreground in video is very important for many applications, such as visual surveillance, objectbased video coding, etc. When objects move with different speeds and under illumination changes, the robustness of moving object detection methods proposed so far is still not satisfactory. In this paper, we use the semantic information to adjust the pixel-wise learning rate adapt...