Computing von Kries Illuminant Changes by Piecewise Inversion of Cumulative Color Histograms

We present a linear algorithm for the computation of the illuminant change occurring between two color pictures of a scene. We model the light variations with the von Kries diagonal transform and we estimate it by minimizing a dissimilarity measure between the piecewise inversions of the cumulative color histograms of the considered images. We also propose a method for illuminant invariant image recognition based on our von Kries transform estimate

Personal Shopping Assistance and Navigator System for Visually Impaired People

International audienceIn this paper, a personal assistant and navigator system for visually impaired people will be described. The showcase presented in-tends to demonstrate how partially sighted people could be aided by the technology in performing an ordinary activity, like going to a mall and moving inside it to find a specific product. We propose an Android ap-plication that integrates Pedestrian Dead Reckoning and Computer Vi-sion algorithms, using an off-the-shelf Smartphone connected to a Smart-watch. The detection, recognition and pose estimation of specific objects or features in the scene derive an estimate of user location with sub-meter accuracy when combined with a hardware-sensor pedometer. The pro-posed prototype interfaces with a user by means of Augmented Reality, exploring a variety of sensorial modalities other than just visual overlay, namely audio and haptic modalities, to create a seamless immersive user experience. The interface and interaction of the preliminary platform have been studied through specific evaluation methods. The feedback gathered will be taken into consideration to further improve the pro-posed system

Video-based technologies for surveillance and monitoring

This contribution presents the surveillance and monitoring technologies developed at the Technologies of Vision (TeV) research unit of the Fondazione Bruno Kessler in Trento (formerly ITC). A brief description of the research conducted in TeV is followed by the introduction of two technologies, devoted to traffic scene analysis (Scoca) and to people tracking (SmarTrack). They represent the result of the research carried on in the context of various projects, which originated demonstrative systems and prototypes. Expressions of interest have been shown by different companies and they are currently undertaking a transfer and exploitation process

A Review on Iconic Indexing for Large Visual Databases

The amount of information stored in form of images, pictures or videos is undergoing a tremendous growth in these years. The developement of techniques for the automatic management of such a bulk of information is becoming a key iussue. This report presents a survey of recent techniques for automatic picture indexing and their application to image retrieval, image reconstruction and spatial reasoning about the objects in the images. Our emphasis is on the 2D string approac

Estimating Illuminant Changes by Piecewise Inversion of Cumulative Color Histograms

We present a new linear algorithm for the computation of the illuminant change occurring between two color images. We approximate the light variations by the von Kries diagonal transform, whose coefficients we estimate by minimizing a dissimilarity measure between the piecewise inversions of the cumulative color histograms of the considered images. We provide an analysis about the accuracy of our estimate and we explain how to use it for illuminant invariant image retrieval

Rotation, Rescaling and Occlusion Invariant Object Retrieval

This paper presents a new approach for rotation, rescaling and occlusion invariant retrieval of the objects of a given database D. The objects are represented by means of many 2D views and each of them is occluded by several half-planes. The remaining visible parts (linear cuts} as well as the whole views are stored in a new database D` and described by low-level features. Given a portion R of an image, the retrieval of the most similar object is done by generating some linear cuts of R, and by comparing their descriptors with those of the elements of D`. Some heuristic rules regarding visual similarity and geometric properties of the objects in the database drive this process. In the case R is recognized as an object partially occluded, a strategy for the reconstruction of the whole shape of R is also presented. The tests carried out on synthetic and real-world datasets showed good performances both in recognition and in reconstruction accuracy

A sampling algorithm for occlusion robust multi target detection

Bayesian methods for visual tracking, with the particle filter as its most prominent instance, have proven to work effectively in the presence of clutter, occlusions, and dynamic background. When applied to track a variable number of targets, however, they become inefficient due to the absence of strong priors. In this paper we present an efficient sampling algorithm for target detection build upon an informed prior that is derived as the inverse of an occlusion robust image likelihood. It has the advantage of being fully integrated in the Bayesian tracking framework, and reactive as it uses sparse features not explained by tracked objects

Illuminant Change Estimation via Minimization of Color Histogram Divergence

We present a new method for computing the change of light possibly occurring between two pictures of the same scene. We approximate the illuminant variation with the von Kries diagonal transform and estimate it by minimizing a functional that measures the divergence between the image color histograms. Our approach shows good performances in terms of accuracy of the illuminant change estimation and of robustness to pixel saturation and Gaussian noise. Moreover we illustrate how the method can be applied to solve the problem of illuminant invariant image recognition

Von Kries Model Under Planckian Illuminants: An Empirical Analysis

This is a technical report, that investigate the relation between two models for describing the variation of the colors due to a photmetric change. Abstract: Planckian illuminants and the von Kries diagonal model are commonly assumed by many computer vision algorithms for modeling the color variations between two images of a same scene captured under two different illuminants. In this work we provide a method to estimate a von Kries transform approximating a Planckian illuminant change and we show that the Planckian assumption constraints the von Kries coefficients to belong to a ruled surface depending on physical cues of the lights. Moreover, we provide an approximated parametric representation of such a surface, making evident the dependence of the von Kries transform on the light color temperature and on the intensity

Planckian Illuminants and Von Kries Model

Technical Report - In this work the authors investigate two hypotheses commonly assumed in Computer Vision and Computer Graphics for solvin In this work the authors investigate the relations between the colors of two pictures of a same scene taken under two different light sources. This is a crucial task in Computer Vision and Computer Graphics. The authors show that: (1) the von Kries model suffices for describing the color variation due to a Planckian illuminant change; (2) the Planck's law constraints the triplets of the von Kries coefficients to be points of a ruled surfaces parametrized by the photometric cues of the illuminants; (3) the von Kries coefficients are strongly related to the sensitivity functions of the device. Several experiments carried out on public image datasets are presented