Research

See the LAMP page for the latest projects.

Fast Bilateral Filtering in Color Images
In this research, we propose a fast approximation to the bilateral filter for color images. The filter is based on two ideas. Firstly, the number of colors which occur in a single natural image is limited. We exploit this color sparseness to rewrite the initial non-linear bilateral filter as a number of linear filter operations. Secondly, we impose a statistical prior to the image values which are locally present within the filter window.
(project page+code)
Multi-Illuminant estimation
We propose a CRF based method for multi-illuminant estimation. In addition we propose a data set with pixelwise ground-truth of both real scenes and laboratroy setting images.
(project page+data set)
Discriminative Color Descriptors
In this work we propose a number of discriminative color descriptors which are optimizing the discriminative power with respect to a classifciation problem. In addition, we propose a set of universal color descriptors which can be used without any prior training on any data set.
(project page + software)
Synthetic image intrinsic image data set
We propose a synthetic image data set for intrinsic image evaluation.
(project page + data set)
Action Recognition in Still Images
We evaluate the usage of color for action recognition in still images.
(project page)
Color object detection
We extend part-based object detection with color information. Results on VOC PASCAL are provided and code is available.
(project page + software)
Compact multi-cue vocabularies
We propose a novel approach for constructing multi-cue Portmanteau vocabularies for image classification.
(project page + software)
Object Recoloring based on Intrinsic Image Estimation
In this research we decompose the image into its intrinsic reflectance components with the aim to recolor scenes.
(project page + software)
Discriminative Pyramids for Object and Scene Recognition
In this research we address the high dimenssionality of spatial pyramids, which is generally considered to be its most serious disadvantage.
(project page + software)
Physics-based color image segmentation
Based on an analysis of the bi-directional reflection model we propose a method which is particularly suited for segmentation in the presence of shadow and highlight edges.
(project page + software)
Color attention for object recognition
We propose a novel image representation where color attention is used to sample the shape description of the image.
(project page + software)
Color Feature Detection for Object Recognition
Luminance edges are still the main source of information in the state-of-the-art methods for feature detection. We propose to exploit the statistical structure of luminance and color in natural images to extract the most discriminative features from the viewpoint of information theory for object recognition.
(project page + software)
Keypoint/Region detection
The project is led by Pedro Martins (University of Coimbra, Portugal), which has been a visiting Ph.D. student at the University of Barcelona. There are two research lines: defining a keypoint extraction procedure based on information theory (1) and introducing a structures highlighting procedure prior to the well known MSER region detector (2, 3) in order to provide stable and complementary regions.