It is common sense among experts that visual attention plays an important role in perception, being necessary for obtaining salient information about the surroundings. It may be the “glue” that binds simple visual features into an object [1]. Having proposed a spatiotemporal model for visual attention in the past, we elaborate on this work and use it for video classification. Our claim is that ...

This paper presents a novel method for detection of image interest regions called Structure Guided Salient Regions (SGSR). Following the information theoretic route to saliency detection, we extend Kadir et al.’s Salient Region detector by exploiting image structure information. The detected SGSRs are highly distinct and very selective. For planar scenes, their performance on repeatability test...

Robust small target detection of low signal-to-noise ratio (SNR) is very important in infrared search and track applications for self-defense or attacks. Due to the complex background, current algorithms have some unsolved issues with false alarm rate. In order to reduce the false alarm rate, an infrared small target detection algorithm based on saliency detection and support vector machine was...

Person re-identification is a challenging task of matching a person’s image across multiple images captured from different camera views. Recently, deep learning based approaches have been proposed that show promising performance on this task. However, most of these approaches use whole image features to compute the similarity between images. This is not very intuitive since not all the regions ...

Intelligent visual surveillance by multiple cameras has becoming more and more important in recent years. A novel and effective method to match objects between multiple cameras is proposed in this work, based on the proposed wavelet salient features. Firstly, the background and foreground is separated based on Gaussian Mixture Model (GMM). To achieve a reliable matching objects between cameras,...

A salient image region is defined as an image part that is clearly different from its surround in terms of a number of attributes. In bottom-up processing, these attributes are defined as: contrast, color difference, brightness, and orientation. By measuring these attributes, visual saliency algorithms aim to predict the regions in an image that would attract our attention under free viewing co...

Most previous works on salient object detection concentrate on 2D images. In this paper, we propose to explore the power of depth cue for predicting salient regions. Our basic assumption is that a salient object tends to stand out from its surroundings in 3D space. To measure the object-to-surrounding contrast, we propose a novel depth feature which works on a single depth map. Besides, we inte...

This paper proposes a novel face recognition algorithm inspired by Human Visual System (HVS). Firstly, we learn where people look by recording observers’ eye movements when they are viewing face images. We find that the observers are consistent in the regions fixated and such fixated regions are selected as the salient regions. Secondly, we represent the face images by four scales of Local Bina...

Salient object detection aims to locate objects that capture human attention within images. Previous approaches often pose this as a problem of image contrast analysis. In this work, we model an image as a hypergraph that utilizes a set of hyperedges to capture the contextual properties of image pixels or regions. As a result, the problem of salient object detection becomes one of finding salie...

We present a method, based on the idea of salient points, for locating corresponding features between two different faces independently of scale, orientation and position. Salient points are those which have a low probability of being mistaken with other points in the face, and therefore are more likely to be correctly located in a second face. The local image structure at each image point is d...