Jacob Scharcanski

Jacob Scharcanski
Universidade Federal do Rio Grande do Sul | UFRGS · Instituto de Informática, Departamento de Informática Aplicada

PhD (U. of Waterloo, Canada, 1993)

About

203
Publications
56,357
Reads
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2,733
Citations
Additional affiliations
September 2015 - present
University of Waterloo
Position
  • Adjunct (Full) Professor
November 2006 - August 2015
University of Waterloo
Position
  • Professor (Associate)
February 2003 - February 2003
The University of Manchester
Position
  • Visiting Professor

Publications

Publications (203)
Article
Full-text available
Face recognition still is a challenging task since face images may be affected by changes in the scene, such as in head pose, face expression, or illumination. Also, face pattern representation often requires several dimensions, which poses additional challenges for face recognition. We propose a novel face recognition method based on projections o...
Article
Full-text available
Yawning detection has a variety of important applications in driver fatigue detection,well-being assessment of humans, driving behaviour monitoring, operator attentiveness detection, and understanding the intentions of a person with a tongue disability. In all of the above applications, automatic detection of yawning is one important system compone...
Article
Full-text available
Diabetic macular edema (DME) affects the retina and reduces the visual acuity of patients with severe diabetic retinopathy. Its conventional treatment involves laser photocoagulation combined with infrared (IR) imaging. However, the laser beam may hit healthy retinal areas and cause unintentional retinal damages if retinal motion occurs. We propose...
Article
Full-text available
This work proposes a simple and yet effective thresholding method to segment pigmented skin lesions in macroscopic photographs automatically. Segmentation is one of the first steps in computer-aided diagnosis of skin cancers. Therefore, an accurate segmentation may play an important clinical role. We develop an algorithm that searches for a thin re...
Article
Full-text available
Discriminating shadows from the objects casting them often is challenging in practice, since the moving targets and their shadows tend to present similar motion patterns, and foreground detection methods often confuse cast shadows with foreground objects. To overcome these shadow detection difficulties, we propose a new stochastic shadow detection...
Article
This paper proposes a novel image-based approach to detect counterfeit medicines and identify the most relevant regions of the tablet in the task of classification. Images of medicine tablets undergo an initial pre-processing step which (i) removes the background to find the region of interest, (ii) clusters individual pixels into super-pixels, and...
Article
Full-text available
Secure user access to devices and datasets is widely enabled by fingerprint or face recognition. Organization of the necessarily large secure digital object datasets, with objects having content that may consist of images, text, video or audio, involves efficient classification and feature retrieval processing. This usually will require multidimens...
Article
Object tracking is challenging and recently correlation filters methods have been proposed for this task. Most of these methods focus on the central portion of the target, and are negatively affected by changes in the target size and shape. This work proposes a collaborative scheme using several local correlation filters combined with a global corr...
Article
Full-text available
In this work, we propose an adaptive face tracking scheme that compensates for possible face tracking errors during its operation. The proposed scheme is equipped with a tracking divergence estimate, which allows to detect early and minimize the face tracking errors, so the tracked face is not missed indefinitely. When the estimated face tracking e...
Conference Paper
Full-text available
Object tracking can be used to localize objects in scenes, and also can be used for locating changes in the object’s appearance or shape over time. Most of the available object tracking methods tend to perform satisfactorily in controlled environments but tend to fail when the objects appearance or shape changes, or even when the illumination chang...
Data
Matlab code and demo for the paper entitled 'Incremental Multi-Model Dictionary Learning for Face Tracking' by A. Khurshid and J. Scharcanski, published at IEEE I2MTC 2018 (Houston, USA, May 2018).
Code
The code contains the implementation in Matlab of the Incremental Multi-model Dictionary Leaning for Face Tracking. It has two models to track the face and facial landmarks which are Motion Model and Appearance Model. The motion model is used to model the movement of the face from one frame to the next frame and provide candidate target face sample...
Thesis
Full-text available
Object tracking can be used to localize objects in scenes, and also can be used for locating changes in the object’s appearance or shape over time. Most of the available object tracking methods tend to perform satisfactorily in controlled environments but tend to fail when the objects appearance or shape changes, or even when the illumination chang...
Article
Full-text available
Land-use classification in very high spatial resolution images is critical in the remote sensing field. Consequently, remarkable efforts have been conducted towards developing increasingly accurate approaches for this task. In recent years, deep learning has emerged as a dominant paradigm for machine learning, and methodologies based on deep convol...
Article
Full-text available
Geodesic distance is a natural dissimilarity measure between probability distributions of a specific type, and can be used to discriminate texture in image-based measurements. Furthermore, since there is no known closed-form solution for the geodesic distance between general multivariate normal distributions, we propose two efficient approximations...
Article
Full-text available
A camera-based scheme is proposed for detecting vehicles at user-defined virtual loops, simulating the operation of inductive loops. False vehicular detections are minimized by a combination of efficient edge detection and color information. The experimental results suggest that the proposed scheme potentially can detect and count vehicles at user-...
Article
Full-text available
This paper presents a novel non-supervised clustering method based on adaptive Bayesian trees (ABT). A Bayesian framework is proposed for seeking modes of the underlying discrete distribution of the input data, and the data is represented by hierarchical clusters found using the adaptive Bayesian trees approach. The application of the proposed clus...
Conference Paper
Full-text available
In this work, a new method based on a multi-model dictionary is proposed for face tracking. A reconstruction and a classification dictionary are combined, and each dictionary is learned from positive and negative examples. This scheme tends to enhance the discrimination between a tracked target face and the background. Also, an efficient scheme tha...
Article
Superpixels have many applications in visual information processing, and can be used to reduce redundant information of an image, as well as the computational complexity of other expensive tasks (e.g., image segmentation). In this work, an Iterative Hierarchical Stochastic Graph Contraction (IHSGC) method for multi-scale superpixels generation is p...
Data
This set of macroscopic images containing pigmented melanocytic skin lesions are digital (non-dermoscopic) images obtained with conventional cameras (e.g. smart phones), which usually have shading areas (i.e., image artifacts/illumination problems) that may be confused with skin lesions. To avoid that such artifacts mislead the segmentation process...
Article
Full-text available
Changing atmospheric conditions often result in a data distribution shift in remote sensing images for different dates and locations making it difficult to discriminate between various classes of interest. To alleviate this data shift issue, we introduce a novel supervised classification framework, called Classify-Normalize-Classify (CNC). The prop...
Data
Matlab code for our paper in Pattern Recognition Letters : Adaptive image denoising and edge enhancement in scale-space using the wavelet transform April 2003 Pattern Recognition Letters DOI: 10.1016/S0167-8655(02)00220-9
Data
This is the Matlab code for 'A simple weighted thresholding method for the segmentation of pigmented skin lesions in macroscopic images" published in Pattern Recognition 64 (2017) 92–104
Conference Paper
Full-text available
Resumo: A tractografia por tensor de difusão (DTI) vem sendo amplamente utilizada como ferramenta qualitativa, tanto na área clínica como em pesquisa científica. Porém, o modelo matemático utilizado tipicamente não representa bem conjuntos de fibras cerebrais quando se cruzam. O presente trabalho investiga o modelo baseado na deconvolução esférica...
Conference Paper
Full-text available
This work presents a novel approach for detecting and classifying melanocytic skin lesions on macroscopic images. We oversegment the skin lesions using superpixels, and classify independently each superpixel as a benign or malignant using local and contextual information. The overall superpixel classification results allow to calculate an index of...
Conference Paper
Full-text available
Computer vision problems often require extracting and handling large volumes of high dimensional data. Commonly, a dimensionality reduction is initially applied to project the features representing the input data into lower dimensionality spaces before its analysis and/or classification. Techniques like Principal Component Analysis (PCA) have been...
Article
Full-text available
The number of vehicles in circulation in modern urban centers has greatly increased, which motivates the development of automatic traffic monitoring systems. Consequently, camera-based traffic monitoring systems are becoming more used widely, since they offer important technological advantages in comparison with traditional traffic monitoring syste...
Article
Full-text available
Bringing computer vision into our daily life has been challenging researchers in industry and in academia over the past decades. However, the continuous development of cameras and computing systems turned computer vision-based measurements into a viable option, allowing new solutions to known problems. In this context, computer vision is a generic...
Article
Full-text available
Pre-screening systems for the diagnosis of melanocytic skin lesions depend of the proper segmentation of the image region affected by the lesion. This paper proposes a feature learning scheme that finds relevant features for skin lesion image segmentation. This work introduces a new unsupervised dictionary learning method, namely Unsupervised Infor...
Article
Full-text available
Background: Lung cancer results in the highest number of cancer deaths worldwide. The segmentation of lung nodules is an important task in computer systems to help physicians differentiate malignant lesions from benign lesions. However, it has already been observed that this may be a difficult task, especially when nodules are connected to an anat...
Code
Matlab code v 1.0 : ’A Coarse-to-fine Approach for Segmenting Melanocytic Skin Lesions in Standard Camera Images’ , Computers Methods and Programs in Biomedicine, vol. 112, pp. 684–693, 2013
Article
Full-text available
p>This work presents an efficient and scalable texture segmentation algorithm based on bag-of-features and stochastic region merging. The image is partitioned into blocks and processed independently to obtain regions, which are then merged to obtain the final segmentation. Experimental results shows the proposed method achieves an overall speed imp...
Article
Full-text available
This work presents a novel unsupervised method to segment skin lesions in macroscopic images, grouping the pixels into three disjoint categories, namely ’skin lesion’, ’suspicious region’ and ’healthy skin’. These skin region categories are obtained by analyzing the agreement of adaptative thresholds applied to the different skin image color channe...
Data
This matlab code refers to the paper 'Image Segmentation via Multi-scale Stochastic Regional Texture Appearance Models', at: https://www.researchgate.net/publication/278050799_Image_Segmentation_via_Multi-scale_Stochastic_Regional_Texture_Appearance_Models
Article
Full-text available
An ongoing challenge in the area of image segmentation is in dealing with scenes exhibiting complex textural characteristics. While many approaches have been proposed to tackle this particular challenge, a related topic of interest that has not been fully explored for dealing with this challenge is stochastic texture models, particularly for charac...
Conference Paper
Full-text available
This paper presents a fast algorithm to segment moving objects in video sequences, as the first step of a fast object tracking system. It is based on the detection of level lines to detect closed objects contours in a scene. The detected objects are clustered using a combination of mean shift and ensemble clustering. The proposed method produces a...
Conference Paper
Full-text available
This paper describes an automated method for segmenting color images based on a modified stochastic region merging strategy with multi-scale spatial constraints. First, a bilateral decomposition is performed, and an over-segmentation process is then performed based multichannel information and multi-scale gradients. Next, each sub-region is represe...
Article
Full-text available
This paper presents a new automatic framework for extracting and characterizing the dynamic shape of the 3D wetting front and its propagation, based in a sequence of tomographic images acquired as water (moisture) in ltrates in unsaturated soils. To the best of the authors' knowledge, the shape of the 3D wetting front and its propagation and progre...
Article
Full-text available
This paper presents a new system for detecting and counting vehicles in urban traffic videos at user-defined virtual loops. The proposed method uses motion coherence and spatial adjacency to group sampling particles in urban vide sequences. A foreground mask is created using Gaussian Mixture Models and Motion Energy Images to determine the preferab...
Conference Paper
Full-text available
Serious games fall under a set of applications capable of improving recovery times by increasing the player's engagement. In this paper we focus on the possibility of joining that capacity to Microsoft Kinect sensors ability to collect data without the need of additional sensorsand present an application capable of giving proper feedback about the...
Conference Paper
Full-text available
Pigmented melanocytic skin lesion pre-screening relies on the proper segmentation of the image regions affected by the skin lesion. This paper proposes a new pigmented melanocytic skin lesion segmentation algorithm for standard camera images. It is assumed that only one skin lesion is in each input image, and also is assumed that the skin lesion is...
Conference Paper
Full-text available
Infrared images sequences of the retina are commonly used for diagnosing diabetic macular edema(DME) and its treatment. Retinal motion detection and its compensation are important steps in the laser treatment of DME. In this paper, we propose to use the phase shift approach and information measures for detecting and compensating retinal motion in i...
Conference Paper
Full-text available
Melanoma is a type of malignant pigmented skin lesion, which currently is among the most dangerous existing cancers. Segmentation is an important step in computer-aided pre-screening systems for pigmented skin lesions, because a good definition of the lesion area and its rim is very important for discriminating between benign and malignant cases. I...
Book
This volume offers a guide to the state of the art in the fast evolving field of biometric recognition to newcomers and experienced practitioners. It is focused on the emerging strategies to perform biometric recognition under uncontrolled data acquisition conditions. The mainstream research work in this field is presented in an organized manner, s...
Chapter
Full-text available
Data, information dimensionality and manifold learning techniques are related issues that are gaining prominence in biometrics. Problems dealing with large amounts of data often have dimensionality issues, leading to uncertainty and inefficiency. This chapter presents concepts of manifold learning and information geometry, and discusses how the man...
Article
Full-text available
Visual monitoring of analogue meters is a critical task especially in isolated locations. Active shape models (ASMs) allow modelling of arbitrary shapes, even when they deform, by a shape adaptive technique. In this study, the authors describe a new ASM scheme for remote reading of panels with multiple analogue displays. Assuming a trained ASM for...
Book
This volume offers a guide to the state of the art in the fast evolving field of biometric recognition to newcomers and experienced practitioners. It is focused on the emerging strategies to perform biometric recognition under uncontrolled data acquisition conditions. The mainstream research work in this field is presented in an organized manner, s...
Chapter
Full-text available
Melanoma is a type of malignant pigmented skin lesion, and currently is among the most dangerous existing cancers. However, differentiating malignant and benign cases is a hard task even for experienced specialists, and a computer-aided diagnosis system can be an useful tool. Usually, the system starts by pre-processing the image, i.e. removing und...
Chapter
Full-text available
The classification of melanocytic skin lesions is a very difficult task, and usually computer-aided diagnosis systems or screening systems focus on reproducing medical criteria as the ABCD rule. However, the texture information can also contribute significantly for the lesion classification, since malignant cases tends to present texture patterns d...
Conference Paper
This paper presents an approach for segmenting natural scenes based on the underlying texture characteristics using a stochastic region merging strategy. Texture region models are constructed from patch-based stochastic texture features using a texton dictionary learning approach. Finally, a stochastic region merging strategy performs the image seg...
Book
The goal of this volume is to summarize the state-of-the-art in the utilization of computer vision techniques in the diagnosis of skin cancer. Malignant melanoma is one of the most rapidly increasing cancers in the world. Early diagnosis is particularly important since melanoma can be cured with a simple excision if detected early. In recent years,...
Article
Full-text available
Feature selection is a key issue in pattern recognition, specially when prior knowledge of the most discriminant features is not available. Moreover, in order to perform the classification task with reduced complexity and acceptable performance, usually features that are irrelevant, redundant, or noisy are excluded from the problem representation....
Article
Full-text available
Melanoma is a type of malignant melanocytic skin lesion, and it is among the most life threatening existing cancers if not treated at an early stage. Computer-aided prescreening systems for melanocytic skin lesions is a recent trend to detect malignant melanocytic skin lesions in their early stages, and lesion segmentation is an important initial p...
Article
Full-text available
In this paper, we propose a novel approach to discriminate malignant melanomas and benign atypical nevi, since both types of melanocytic skin lesions have very similar characteristics. Recent studies involving the non-invasive diagnosis of melanoma indicate that the concentrations of the two main classes of melanin present in the human skin, eumela...
Article
Full-text available
Infrared image data captured by non-mydriatic digital retinography systems often are used in the diagnosis and treatment of the diabetic macular edema (DME). Infrared illumination is less aggressive to the patient retina, and retinal studies can be carried out without pupil dilation. However, sequences of infrared eye fundus images of static scenes...
Conference Paper
Full-text available
This work presents a novel method for skin detection as a pre-processing step for (hand) gesture segmentation. First, the skin color and texture models are learnt from a training set of skin images, where a Gaussian Mixture Model (GMM) and texton dictionary is constructed. Then, a stochastic region merging strategy is used to segment the image text...