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Subject = Computer vision;
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Displaying Results 1 - 22 of 22 on page 1 of 1
Marked
Mark
A multi-modal dance corpus for research into interaction between humans in virtual environments
(2012)
Essid, Slim; Lin, Xinyu; Gowing, Marc; Kordelas, Georgios; Aksay, Anil; Kelly, Philip; ...
A multi-modal dance corpus for research into interaction between humans in virtual environments
(2012)
Essid, Slim; Lin, Xinyu; Gowing, Marc; Kordelas, Georgios; Aksay, Anil; Kelly, Philip; Fillon, Thomas; Zhang, Qianni; Dielmann, Alfred; Kitanovski, Vlado; Tournemenne, Robin; Masurelle, Aymeric; Izquierdo, Ebroul; O'Connor, Noel E.; Daras, Petros; Richard, Gaël
Abstract:
We present a new, freely available, multimodal corpus for research into, amongst other areas, real-time realistic interaction between humans in online virtual environments. The specific corpus scenario focuses on an online dance class application scenario where students, with avatars driven by whatever 3D capture technology is locally available to them, can learn choreographies with teacher guidance in an online virtual dance studio. As the dance corpus is focused on this scenario, it consists of student/teacher dance choreographies concurrently captured at two different sites using a variety of media modalities, including synchronised audio rigs, multiple cameras, wearable inertial measurement devices and depth sensors. In the corpus, each of the several dancers performs a number of fixed choreographies, which are graded according to a number of specific evaluation criteria. In addition, ground-truth dance choreography annotations are provided. Furthermore, for unsynchronised senso...
http://doras.dcu.ie/17916/
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Mark
A system for teaching sign language using live gesture feedback
(2008)
Kelly, Daniel; McDonald, John; Markham, Charles
A system for teaching sign language using live gesture feedback
(2008)
Kelly, Daniel; McDonald, John; Markham, Charles
Abstract:
This paper presents a computer vision based virtual learning environment for teaching communicative hand gestures used in Sign Language. A virtual learning environment was developed to demonstrate signs to the user. The system then gives real time feedback to the user on their performance of the demonstrated sign. Gesture features are extracted from a standard web-cam video stream and shape and trajectory matching techniques are applied to these features to determine the feedback given to the user.
http://mural.maynoothuniversity.ie/8343/
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A unified system for segmentation and tracking of face and hands in sign language recognition
(2006)
Awad, George M.; Han, Junwei; Sutherland, Alistair
A unified system for segmentation and tracking of face and hands in sign language recognition
(2006)
Awad, George M.; Han, Junwei; Sutherland, Alistair
Abstract:
This paper presents a unified system for segmentation and tracking of face and hands in a sign language recognition using a single camera. Unlike much related work that uses colour gloves, we detect skin by combining 3 useful features: colour, motion and position. These features together, represent the skin colour pixels that are more likely to be foreground pixels and are within a predicted position range. We extend the previous research in occlusion detection to handle occlusion between any of the skin objects using a Kalman filter based algorithm. The tracking improves the segmentation by reducing the search space and the segmentation enhances the overall tracking process. The algorithm is tested on several video sequences from a standard database and can provide a very low error rate
http://doras.dcu.ie/225/
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Automated packing systems - a systems engineering approach
(1996)
Whelan, Paul F.; Batchelor, Bruce G.
Automated packing systems - a systems engineering approach
(1996)
Whelan, Paul F.; Batchelor, Bruce G.
Abstract:
The ability to manipulate previously unseen objects under visual control is one of the key tasks in the successful implementation of robotic, automated assembly and adaptive material handling systems. The automation of such complex industrial environments will require the development of machine vision systems that are highly adaptable and capable of dealing with a wide range of variable products. An important group of applications of this type is found in the automated packing and nesting of arbitrary shapes. The aim of this work has been to produce an efficient packing strategy that is flexible enough for a wide variety of industrial uses and which can be implemented using fast moderately priced hardware. A systems approach, as distinct from a purely algorithmic one, has been deliberately adopted since the work is concerned with industrial vision applications in which significant problem constraints exist. This paper also outlines the background to this research, and reviews a sele...
http://doras.dcu.ie/2452/
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Bayesian fusion of hidden Markov models for understanding bimanual movements
(2004)
Shamaie, Atid; Sutherland, Alistair
Bayesian fusion of hidden Markov models for understanding bimanual movements
(2004)
Shamaie, Atid; Sutherland, Alistair
Abstract:
Understanding hand and body gestures is a part of a wide spectrum of current research in computer vision and human-computer interaction. A part of this can be the recognition of movements in which the two hands move simultaneously to do something or imply a meaning. We present a Bayesian network for fusing hidden Markov models in order to recognise a bimanual movement. A bimanual movement is tracked and segmented by a tracking algorithm. Hidden Markov models are assigned to the segments in order to learn and recognize the partial movement within each segment. A Bayesian network fuses the HMMs in order to perceive the movement of the two hands as a single entity.
http://doras.dcu.ie/243/
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Classification of Human Poses using a Vision based Technique
(2007)
Kelly, Dan; Olivo, Paolo; Markham, Charles; McDonald, John; Caulfield, Brian; Fitzgeral...
Classification of Human Poses using a Vision based Technique
(2007)
Kelly, Dan; Olivo, Paolo; Markham, Charles; McDonald, John; Caulfield, Brian; Fitzgerald, Diarmuid
Abstract:
This paper presents work being carried out to estimate human pose using vision based methods. The data acquisition system uses an active marker technique synchronized with a three camera stereo vision system. The locations of the markers are then used to reconstruct a skeleton representation of the human pose. PCA and clustering techniques are used to classify the pose.
http://mural.maynoothuniversity.ie/8348/
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Creating virtual models from uncalibrated camera views
(2004)
Brisc, Felicia; Whelan, Paul F.
Creating virtual models from uncalibrated camera views
(2004)
Brisc, Felicia; Whelan, Paul F.
Abstract:
The reconstruction of photorealistic 3D models from camera views is becoming an ubiquitous element in many applications that simulate physical interaction with the real world. In this paper, we present a low-cost, interactive pipeline aimed at non-expert users, that achieves 3D reconstruction from multiple views acquired with a standard digital camera. 3D models are amenable to access through diverse representation modalities that typically imply trade-offs between level of detail, interaction, and computational costs. Our approach allows users to selectively control the complexity of different surface regions, while requiring only simple 2D image editing operations. An initial reconstruction at coarse resolution is followed by an iterative refining of the surface areas corresponding to the selected regions.
http://doras.dcu.ie/4648/
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Deep learning for texture and dynamic texture analysis
(2017)
Andrearczyk, Vincent
Deep learning for texture and dynamic texture analysis
(2017)
Andrearczyk, Vincent
Abstract:
Texture is a fundamental visual cue in computer vision which provides useful information about image regions. Dynamic Texture (DT) extends the analysis of texture to sequences of moving scenes. Classic approaches to texture and DT analysis are based on shallow hand-crafted descriptors including local binary patterns and filter banks. Deep learning and in particular Convolutional Neural Networks (CNNs) have significantly contributed to the field of computer vision in the last decade. These biologically inspired networks trained with powerful algorithms have largely improved the state of the art in various tasks such as digit, object and face recognition. This thesis explores the use of CNNs in texture and DT analysis, replacing classic hand-crafted filters by deep trainable filters. An introduction to deep learning is provided in the thesis as well as a thorough review of texture and DT analysis methods. While CNNs present interesting features for the analysis of textures such as a d...
http://doras.dcu.ie/22040/
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Detecting shadows and low-lying objects in indoor and outdoor scenes using homographies
(2005)
Kelly, Philip; Beardsley, Paul; Cooke, Eddie; O'Connor, Noel E.; Smeaton, Alan F.
Detecting shadows and low-lying objects in indoor and outdoor scenes using homographies
(2005)
Kelly, Philip; Beardsley, Paul; Cooke, Eddie; O'Connor, Noel E.; Smeaton, Alan F.
Abstract:
Many computer vision applications apply background suppression techniques for the detection and segmentation of moving objects in a scene. While these algorithms tend to work well in controlled conditions they often fail when applied to unconstrained real-world environments. This paper describes a system that detects and removes erroneously segmented foreground regions that are close to a ground plane. These regions include shadows, changing background objects and other low-lying objects such as leaves and rubbish. The system uses a set-up of two or more cameras and requires no 3D reconstruction or depth analysis of the regions. Therefore, a strong camera calibration of the set-up is not necessary. A geometric constraint called a homography is exploited to determine if foreground points are on or above the ground plane. The system takes advantage of the fact that regions in images off the homography plane will not correspond after a homography transformation. Experimental results us...
http://doras.dcu.ie/283/
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Enriching the fan experience in a smart stadium using internet of things technologies
(2017)
Panchanathan, Sethuraman; Chakraborty, Shayok; McDaniel, Troy; Tadayon, Ramin; Fakhri, ...
Enriching the fan experience in a smart stadium using internet of things technologies
(2017)
Panchanathan, Sethuraman; Chakraborty, Shayok; McDaniel, Troy; Tadayon, Ramin; Fakhri, Bijan; O'Connor, Noel E.; Marsden, Mark; Little, Suzanne; McGuinness, Kevin; Monaghan, David
Abstract:
Rapid urbanization has brought about an influx of people to cities, tipping the scale between urban and rural living. Population predictions estimate that 64% of the global population will reside in cities by 2050. To meet the growing resource needs, improve management, reduce complexities, and eliminate unnecessary costs while enhancing the quality of life of citizens, cities are increasingly exploring open innovation frameworks and smart city initiatives that target priority areas including transportation, sustainability, and security. The size and heterogeneity of urban centers impede progress of technological innovations for smart cities. We propose a Smart Stadium as a living laboratory to balance both size and heterogeneity so that smart city solutions and Internet of Things (IoT) technologies may be deployed and tested within an environment small enough to practically trial but large and diverse enough to evaluate scalability and efficacy. The Smart Stadium for Smart Living i...
http://doras.dcu.ie/21873/
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Hand tracking and bimanual movement understanding
(2003)
Shamaie, Atid
Hand tracking and bimanual movement understanding
(2003)
Shamaie, Atid
Abstract:
Bimanual movements are a subset ot human movements in which the two hands move together in order to do a task or imply a meaning A bimanual movement appearing in a sequence of images must be understood in order to enable computers to interact with humans in a natural way This problem includes two main phases, hand tracking and movement recognition. We approach the problem of hand tracking from a neuroscience point ot view First the hands are extracted and labelled by colour detection and blob analysis algorithms In the presence of the two hands one hand may occlude the other occasionally Therefore, hand occlusions must be detected in an image sequence A dynamic model is proposed to model the movement of each hand separately Using this model in a Kalman filtering proccss the exact starting and end points of hand occlusions are detected We exploit neuroscience phenomena to understand the beha\ tour of the hands during occlusion periods Based on this, we propose a general hand trackin...
http://doras.dcu.ie/18221/
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Inspection of the integrity of surface mounted integrated circuits on a printed circuit board using vision
(1991)
Yakoub, Imad
Inspection of the integrity of surface mounted integrated circuits on a printed circuit board using vision
(1991)
Yakoub, Imad
Abstract:
Machine vision technology has permeated many areas of industry, and automated inspection systems are playing increasingly important roles in many production processes. Electronic manufacturing is a good example of the integration of vision based feedback in manufacturing and the assembly of surface mount PCBs is typical of the technology involved. There are opportunities to use machine vision during different stages of the surface mount process. The problem in the inspection of solder joints on surface mount printed circuit board is much more difficult than many other inspection problems. In this thesis, an approach for inspecting surface mounted integrated circuits (SMICs) is presented. It is based on the variance of intensity values of pixels in an image. This method is able to cope with 4 kinds of soldering defects in SMICs. A set of modules for the system is proposed. The computer program which performs the image processing and analyzing has been written in C. It has been link...
http://doras.dcu.ie/19490/
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Intelligent vision systems for industry
(1997)
Batchelor, Bruce G.; Whelan, Paul F.
Intelligent vision systems for industry
(1997)
Batchelor, Bruce G.; Whelan, Paul F.
http://doras.dcu.ie/18215/
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Modelling, classification and synthesis of facial expressions
(2008)
Reilly, Jane; Ghent, John; McDonald, John
Modelling, classification and synthesis of facial expressions
(2008)
Reilly, Jane; Ghent, John; McDonald, John
Abstract:
The field of computer vision endeavours to develop automatic approaches to the interpretation of images from the real world. Over the past number of decades researchers within this field have created systems specifically for the automatic analysis of facial expression. The most successful of these approaches draw on the tools from behavioural science. In this chapter we examine facial expression analysis from both a behavioural science and a computer vision perspective. First we will provide details of the principal approach used in behavioural science to analyze facial expressions. This will include an overview of the evolution of facial expression analysis, where we introduce the field of facial expression analysis with Darwin’s initial findings (Darwin, 1872). We then go on to show how his findings were confirmed nearly 100 years later by Ekman et al. (Ekman et al., 1969). Following on from this we provide details of recent works investigating the appearance and dynamics of facia...
http://mural.maynoothuniversity.ie/8256/
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Non-Linear Approaches for the Classification of Facial Expressions at Varying Degrees of Intensity
(2007)
Reilly, Jane; Ghent, John; McDonald, John
Non-Linear Approaches for the Classification of Facial Expressions at Varying Degrees of Intensity
(2007)
Reilly, Jane; Ghent, John; McDonald, John
Abstract:
The research discussed in this paper documents a comparative analysis of two nonlinear dimensionality reduction techniques for the classification of facial expressions at varying degrees of intensity. These nonlinear dimensionality reduction techniques are Kernel Principal Component Analysis (KPCA) and Locally Linear Embedding (LLE). The approaches presented in this paper employ psychological tools, computer vision techniques and machine learning algorithms. In this paper we concentrate on comparing the performance of these two techniques when combined with Support Vector Machines (SVMs) at the task of classifying facial expressions across the full expression intensity range from near-neutral to extreme facial expression. Receiver Operating Characteristic (ROC) curve analysis is employed as a means of comprehensively comparing the results of these techniques.
http://mural.maynoothuniversity.ie/8345/
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Reduction of false alarms triggered by spiders/cobwebs in surveillance camera networks.
(2016)
Hebbalaguppe, Ramya; McGuinness, Kevin; Kuklyte, Jogile; Albatal, Rami; Direkoglu, Cem;...
Reduction of false alarms triggered by spiders/cobwebs in surveillance camera networks.
(2016)
Hebbalaguppe, Ramya; McGuinness, Kevin; Kuklyte, Jogile; Albatal, Rami; Direkoglu, Cem; O'Connor, Noel E.
Abstract:
The percentage of false alarms caused by spiders in automated surveillance can range from 20-50%. False alarms increase the workload of surveillance personnel validating the alarms and the maintenance labor cost associated with regular cleaning of webs. We propose a novel, cost effective method to detect false alarms triggered by spiders/webs in surveillance camera networks. This is accomplished by building a spider classifier intended to be a part of the surveillance video processing pipeline. The proposed method uses a feature descriptor obtained by early fusion of blur and texture. The approach is sufficiently efficient for real-time processing and yet comparable in performance with more computationally costly approaches like SIFT with bag of visual words aggregation. The proposed method can eliminate 98.5% of false alarms caused by spiders in a data set supplied by an industry partner, with a false positive rate of less than 1%
http://doras.dcu.ie/21420/
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Robust Feature Correspondences from a Large Set of Unsorted Wide Baseline Images
(2009)
Cao, Yanpeng; McDonald, John
Robust Feature Correspondences from a Large Set of Unsorted Wide Baseline Images
(2009)
Cao, Yanpeng; McDonald, John
Abstract:
Given a set of unordered images taken in a wide area, an effective solution is proposed for establishing robust feature correspondences among them. Two major improvements are made in our work as follows: firstly, a robust technique is proposed for the self-organization of a large number of images without spatial orderings; secondly, a novel wide-baseline matching approach is developed to obtain good correspondences over images taken from substantially different viewpoints. The output consists of many sets of reliable pair-wise feature correspondences which are essential in various computer vision applications. Realistic experiments were carried out to evaluate the performances of the proposed method by using a large amount of images captured from our university’s campus.
http://mural.maynoothuniversity.ie/2326/
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Speech-conditioned face generation using generative adversarial networks
(2019)
Duarte, Amanda; Roldan, Francisco; Tubau, Miquel; Escur, Janna; Pascual, Santiago; Salv...
Speech-conditioned face generation using generative adversarial networks
(2019)
Duarte, Amanda; Roldan, Francisco; Tubau, Miquel; Escur, Janna; Pascual, Santiago; Salvador, Amaia; Mohedano, Eva; McGuinness, Kevin; Torres, Jordi; Giró-i-Nieto, Xavier
Abstract:
Speech is a rich biometric signal that contains information about the identity, gender and emotional state of the speaker. In this work, we explore its potential to generate face images of a speaker by conditioning a Generative Adversarial Network (GAN) with raw speech input. We propose a deep neural network that is trained from scratch in an end-to-end fashion, generating a face directly from the raw speech waveform without any additional identity information (e.g reference image or one-hot encoding). Our model is trained in a self-supervised fashion by exploiting the audio and visual signals naturally aligned in videos. With the purpose of training from video data, we present a novel dataset collected for this work, with high-quality videos of ten youtubers with notable expressiveness in both the speech and visual signals.
http://doras.dcu.ie/23188/
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Team behaviour analysis in sports using the poisson equation
(2012)
Direkoglu, Cem; O'Connor, Noel E.
Team behaviour analysis in sports using the poisson equation
(2012)
Direkoglu, Cem; O'Connor, Noel E.
Abstract:
We propose a novel physics-based model for analysing team play- ers’ positions and movements on a sports playing field. The goal is to detect for each frame the region with the highest population of a given team’s players and the region towards which the team is moving as they press for territorial advancement, termed the region of intent. Given the positions of team players from a plan view of the playing field at any given time, we solve a particular Poisson equation to generate a smooth distribution. The proposed distribu- tion provides the likelihood of a point to be occupied by players so that more highly populated regions can be detected by appropriate thresholding. Computing the proposed distribution for each frame provides a sequence of distributions, which we process to detect the region of intent at any time during the game. Our model is evalu- ated on a field hockey dataset, and results show that the proposed approach can provide effective features that could be used to g...
http://doras.dcu.ie/17546/
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The AXES PRO video search system
(2013)
McGuinness, Kevin; O'Connor, Noel E.; Aly, Robin; de Jong, Franciska; Chatfield, K...
The AXES PRO video search system
(2013)
McGuinness, Kevin; O'Connor, Noel E.; Aly, Robin; de Jong, Franciska; Chatfield, Ken; Parkhi, Omkar M.; Arandjelovic, Relja; Zisserman, Andrew; Douze, Matthijs; Schmid, Cordelia
Abstract:
We demonstrate a multimedia content information retrieval engine developed for audiovisual digital libraries targeted at media professionals. It is the first of three multimedia IR systems being developed by the AXES project. The system brings together traditional text IR and state-of-the-art content indexing and retrieval technologies to allow users to search and browse digital libraries in novel ways. Key features include: metadata and ASR search and filtering, on-the-fly visual concept classification (categories, faces, places, and logos), and similarity search (instances and faces).
http://doras.dcu.ie/17861/
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Vision-based analysis of pedestrian traffic data
(2008)
Kelly, Philip; O'Connor, Noel E.
Vision-based analysis of pedestrian traffic data
(2008)
Kelly, Philip; O'Connor, Noel E.
Abstract:
Reducing traffic congestion has become a major issue within urban environments. Traditional approaches, such as increasing road sizes, may prove impossible in certain scenarios, such as city centres, or ineffectual if current predictions of large growth in world traffic volumes hold true. An alternative approach lies with increasing the management efficiency of pre-existing infrastructure and public transport systems through the use of Intelligent Transportation Systems (ITS). In this paper, we focus on the requirement of obtaining robust pedestrian traffic flow data within these areas. We propose the use of a flexible and robust stereo-vision pedestrian detection and tracking approach as a basis for obtaining this information. Given this framework, we propose the use of a pedestrian indexing scheme and a suite of tools, which facilitates the declaration of user-defined pedestrian events or requests for specific statistical traffic flow data. The detection of the required events or ...
http://doras.dcu.ie/4715/
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Visual perception an information-based approach to understanding biological and artificial vision
(1992)
Murphy, Noel
Visual perception an information-based approach to understanding biological and artificial vision
(1992)
Murphy, Noel
Abstract:
The central issues of this dissertation are (a) what should we be doing — what problems should we be trying to solve — in order to build computer vision systems, and (b) what relevance biological vision has to the solution of these problems. The approach taken to tackle these issues centres mostly on the clarification and use of information-based ideas, and an investigation into the nature of the processes underlying perception. The primary objective is to demonstrate that information theory and extensions of it, and measurement theory are powerful tools in helping to find solutions to these problems. The quantitative meaning of information is examined, from its origins in physical theories, through Shannon information theory, Gabor representations and codes towards semantic interpretations of the term. Also the application of information theory to the understanding of the developmental and functional properties of biological visual systems is discussed. This includes a review of t...
http://doras.dcu.ie/19121/
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