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The use of strong lighting contrast to accentuate objects and figures in a painting—called Chiaroscuro—is popular among Renaissance painters such as Caravaggio, La Tour and Rembrandt. In this paper, we propose a new metric called LuCo to quantify the extent to which Chiaroscuro is employed by an artist in a painting. This measurement could be used to assess the capability of any system to fulfill...
A comparative analysis of 3×3 pixel robust detector and Harris detector in terms of stability and performance detection in case of viewing conditions change caused by the collection and conversion of image cameras presented. The efficiency of detectors was evaluated in terms of the repeatability of feature detection on a different pair of images when the conditions of observation, camera parameters...
Coin segmentation, or separating the coin area from its background, is inevitably the first step in any robust classification method. Yet, the fact that almost every research relies exclusively on grayscale images taken in controlled environments, with uniform illumination and backgrounds, wastes a vast asset of images commonly taken by numismatists, sellers and collectors. Admittedly, very often...
This paper presents a statistical treatment of background modeling for use in target detection, where the global information and local information is added into the statistical framework to construct a robust background model to achieve accurate object detection results. Specifically, a novel self-adaptive Gaussian mixture model is proposed to construct a statistical background model based on the...
Given a non-cooperative, continuous game, we describe a framework for parametric utility learning. Using heteroskedasticity inference, we adapt a Constrained Feasible Generalized Least Squares (cFGLS) utility learning method in which estimator variance is reduced, unbiased, and consistent. We extend our utility learning method using bootstrapping and bagging. We show the performance of the proposed...
After thirty years of researching, the photometric stereo technique for 3D shape recovery still does not provide reliable results if it is not constrained into very well-controlled scenarios. In fact, dealing with realistic materials and lightings yields a non-linear bidirectional reflectance distribution function which is primarily difficult to parametrize and then arduous to solve. With the aim...
Single face-image comparisons are extremely challenging, particularly in the context of pose, expression variations and scene illumination changes. Most of the existing schemes are sub-space learning based, where dominant eigen-directions are determined from the covariance matrix computed over the entire face space. In this paper we propose a simple hashing method based on the relative magnitudes...
In the recent years, human activity recognition is considered to be very important in video analysis researches due to the extensive requests from numerous users in different fields, such as public area surveillance, entertainment, human machine interaction and healthcare systems. In this work, we present a comparative study of two space-time interest points' detectors. These two detectors are evaluated...
The increasing demand for urban mobility calls for a robust real-time traffic monitoring system. In this paper we present a vision-based approach for road traffic density estimation which forms the fundamental building block of traffic monitoring systems. Existing techniques based on vehicle counting and tracking suffer from low accuracy due to sensitivity to illumination changes, occlusions, congestions...
A novel multi-criteria optimization framework for matching of partially visible shapes in multiple images using joint geometric graph embedding is proposed. The proposed framework achieves matching of partial shapes in images that exhibit extreme variations in scale, orientation, viewpoint and illumination and also instances of occlusion; conditions which render impractical the use of global contour-based...
Anthropology studies discover that some genetic related facial features, which are inherited by children from their parents, can be used for kinship verification. This paper investigates an important inheritable feature — color and presents a novel inheritable color space (InCS) and a generalized InCS (GInCS) framework with application to kinship verification. Specifically, a novel color similarity...
Manual analysis of body poses of bed-ridden patients requires staff to continuously track and record patient poses. Two limitations in the dissemination of pose-related therapies are scarce human resources and unreliable automated systems. This work addresses these issues by introducing a new method and a new system for robust automated classification of sleep poses in an Intensive Care Unit (ICU)...
The methodology for finding the same individual in a network of cameras must deal with significant changes in appearance caused by variations in illumination, viewing angle and a person's pose. Re-identification requires solving two fundamental problems: (1) determining a distance measure between features extracted from different cameras that copes with illumination changes (metric learning); and...
An existing deep learning architecture has been adapted to solve the detection problem in camera-based tracking for augmented reality (AR). A known target, in this case a planar object, is rendered under various viewing conditions including varying orientation, scale, illumination and sensor noise. The resulting corpus is used to train a convolutional neural network to match given patches in an incoming...
Face recognition (FR) via regression analysis based classification has been widely applied in the past several years. In the existing regression methods, the testing image is represented as a linear combination of the training samples and the error image is converted into vector which is characterized by l1-norm or l2-norm. Therefore the two-dimensional structure of the error image is neglected in...
Recently the use of QR code for data coding becomes significantly increasing especially for coding identity, health and other specific data. Since some types of data such as identity, health, etc is private data then it needs to be further authenticated. Furthermore, the owner of the identity should be authenticated as well. Therefore, we have to insert biometric features which will be further authenticated...
Specular reflection removal is indispensable to many computer vision tasks. However, most existing methods fail or degrade in complex real scenarios for their individual drawbacks. Benefiting from the light field imaging technology, this paper proposes a novel and accurate approach to remove specularity and improve image quality. We first capture images with specularity by the light field camera (Lytro...
In computer vision application object tracking is a challenging problem. Illumination and occlusion are major constraints observed in object tracking. We are focusing on object tracking with partial or full occlusion. Object tracking is done using features like colors and contours. We have proposed a robust Color-based algorithm to track the object and handle occlusion in real time domain. In our...
This paper presents a large-scale evaluation of a visual localisation method in a challenging city environment. Our system makes use of a map built by combining data from LIDAR and cameras mounted on a survey vehicle to build a dense appearance prior of the environment. We then localise by minimising the normalised information distance (NID) between a live camera image and an image generated from...
The paper proposes a robust three-view matching method to produce quasi-dense 3D points in multi-view stereo. In order to overcome the limitations of traditional wide baseline match propagation methods, the proposed method simultaneously models illumination variations and perspective distortions in images, and performs an effective affine parameter error detection and rectification mechanism in the...
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