Texture features for object salience

Visual Attention Region Detection Using Texture, Object Features

Human perception tends to firstly pick attended regions, which correspond to prominent objects in an image. Visual attention region detection simulates the behavior of the human visual system (HVS) and detects regions of interest (ROIs) in the image. In this study, a visual attention region detection approach using low-level texture and object features is proposed. The new and improved (shifted...

Texture fading correlates with stimulus salience

Perceptual fading of texture targets on similarly textured backgrounds was studied in relation to stimulus salience using texture patterns defined by orientation contrast, shape contrast, and order contrast. In two independent experiments, perceptual salience of the targets was determined. In the first, the textural contrast of the stimuli was varied and their salience quantified using magnitud...

Projected Texture for Object Classification

Algorithms for classification of 3D objects either recover the depth information lost during imaging using multiple images, structured lighting, image cues, etc. or work directly the images for classification. While the latter class of algorithms are more efficient and robust in comparison, they are less accurate due to the lack of depth information. We propose the use of structured lighting pa...

A Parametric Spectral Model for Texture-Based Salience

We present a novel saliency mechanism based on texture. Local texture at each pixel is characterised by the 2D spectrum obtained from oriented Gabor filters. We then apply a parametric model and describe the texture at each pixel by a combination of two 1D Gaussian approximations. This results in a simple model which consists of only four parameters. These four parameters are then used as featu...

BRIEF Features for Texture Segmentation