This paper proposes a novel approach to encode cross-channel texture correlation for color texture classification task. Firstly, we quantitatively study the correlation between different color channels using Local Binary Pattern (LBP) as the texture descriptor and using Shannon’s information theory to measure the correlation. We find that (R, G) channel pair exhibits stronger correlation than (...

Many recent applications using local image features focus on 2D image recognition. Such applications can not distinguish between real objects and photos of objects. In this project, we present a 3D object recognition method using stereo images. Using the 3D information of the objects obtained from stereo images, objects with similar image description but different 3D shapes can be distinguished...

The purpose of this paper is to show how the edge histogram descriptor for image that can be efficiently utilized for image matching. Since the edge histogram descriptor recommended for the standard represents only local edge distribution in an image, the matching performance for image retrieval may not be satisfactory. In this paper, to increase the matching performance, we propose to use the ...

Local Binary Pattern (LBP) is invariant to the monotonic changes in the grey scale domain. This property enables LBP to present a texture descriptor that can be useful in applications dealing with the local illumination changes. However, the existing versions of LBP are not able to handle image illumination changes, especially in outdoor environments. These non-patterned illumination changes di...

In this paper we introduce the concept of local label descriptor, which is a concatenation of label histograms for each cell in a patch. Local label descriptors alleviate the label patch misalignment issue in combining structured label predictions for semantic image labeling. Given an input image, we solve for a label map whose local label descriptors can be approximated as a sparse convex comb...

Approach we have tested in our submitted runs. Our approach consists in finding links between video shot key-frames, based on the use of a probabilistic latent space model over local matches between the keyframe images. This allows the extraction of significant groups of local matching descriptors that may represent common characteristic elements of near duplicate key-frames. This is combined w...