In this paper, we address the general problem of image/object categorization with a novel approach referred to as Bag-of-Scenes (BoS).Our approach is efficient for low semantic applications such as texture classification as well as for higher semantic tasks such as natural scenes recognition or fine-grained visual categorization (FGVC). It is based on the widely used combination of i) Sparse co...

Pyramid Histogram of Multi-scale Block Local Binary Pattern (PH-MBLBP) descriptor for recognizing scene categories, is presented in this paper. We show that scene categorization, especially for indoor and outdoor environments, requires its visual descriptor to process properties that are different from other vision domains (e.g., SIFT descriptor used for object categorization). Our proposed PH-...

In this paper, we present a novel approach to automatic 3D Facial Expression Recognition (FER) based on deep representation of facial 3D geometric and 2D photometric attributes. A 3D face is firstly represented by its geometric and photometric attributes, including the geometry map, normal maps, normalized curvature map and texture map. These maps are then fed into a pre-trained deep convolutio...

In this paper, we present the learning strategies and feature extraction techniques that were applied by the IBM Research Australia team to the Medical Clustering challenge of ImageCLEF 2015. The challenge is to automatically annotate and categorize X-ray images into head-neck, body, upper-limb, lower-limb and foreign object categories. Our proposed methodology and details of experiments for ea...

Horizon line detection is a segmentation problem where a boundary between a sky and non-sky region is searched. Conventionally edge detection is performed as the first step followed by dynamic programming to find the shortest path which conforms to the detected horizon line. Recent work has proposed the use of machine learning to reduce the number of non-horizon edges to accurately detect the h...

Content-Based Image Retrieval (CBIR) system is rising as a crucial analysis space wherever the users will search and retrieve pictures supported by the properties like shape, color and texture from the image information. Typically texture-based image retrieval is taken into account as a clever image of coarseness, dissimilarity and roughness however there's a lot of texture data within the edge...

This paper presents a boundary-based, topological shape descriptor: the distance profile. It is inspired by the LBP (= local binary pattern) scale space – a topological shape descriptor computed by a filtration with concentric circles around a reference point. For rigid objects, the distance profile is computed by the Euclidean distance of each boundary pixel to a reference point. A geodesic di...

We present a comprehensive evaluation of performance of visual feature representations for MediaEval 2011 Violent Scenes Detection Task. As for global features, color moments, color histogram, edge orientation histogram, and local binary patterns are used. As for local features, keypoint detectors such as Harris Laplace, Hessian Laplace, Harris Affine, Dense Sampling are used to extract keypoin...

Local primitives are useful in the analysis, recognition and retrieval of document and patent images. In this paper, local primitives are classified in 4 and 8-directional spaces at optimally detected junction and end points by using a distance based approach. Local primitives are quantized by using a variant of Local Binary Patterns. Spatial relationships between local primitives are establish...