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Current Search:
All of 'Image' and 'processing' in all fields;
366 items found
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Displaying Results 76 - 100 of 366 on page 4 of 15
Marked
Mark
Image segmentation using the double Markov random field, with application to land use estimation
(2001)
WILSON, SIMON PAUL
Image segmentation using the double Markov random field, with application to land use estimation
(2001)
WILSON, SIMON PAUL
Abstract:
peer-reviewed
We describe the double Markov random field, a natural hierarchical model for a Bayesian approach to model-based textured image segmentation. The model is difficult to implement, even using Markov chain Monte Carlo (MCMC) methods, so we describe an approximation that is computationally feasible. This is applied to a satellite image. We emphasise the valuable additional information about uncertainties in the segmentation that can be gained from the use of MCMC.
http://hdl.handle.net/2262/32970
Marked
Mark
On color texture normalization for active appearance models
(2009)
Ionita, Mircea C.; Corcoran, Peter M.; Buzuloiu, Vasile
On color texture normalization for active appearance models
(2009)
Ionita, Mircea C.; Corcoran, Peter M.; Buzuloiu, Vasile
Abstract:
The extension of the standard grayscale active appearance model (AAM) techniques to color images is investigated. Prior work in this field has mainly focused on RGB color models which did not demonstrate noticeable benefits over grayscale models from the point of view of convergence accuracy. We improve on previous work by normalizing the color texture vector separately for intensity and chromaticity components. Where an appropriate color space is chosen, we demonstrate improvements in convergence accuracy as well as image synthesization quality for AAMs. Optimal results are achieved when a color space in which the image channels are strongly decorrelated is chosen. Our best results are achieved using the I1I2I3 color space, originally proposed by Ohta.
http://hdl.handle.net/10379/1350
Marked
Mark
Fourier Descriptors as A General Classification Tool for Topographic Shapes
(1999)
Keyes, L.; Winstanley, Adam C.
Fourier Descriptors as A General Classification Tool for Topographic Shapes
(1999)
Keyes, L.; Winstanley, Adam C.
Abstract:
Automatic structuring (feature coding and object recognition) of topographic data, such as that derived from air survey or raster scanning large scale paper maps, requires the classification of objects such as buildings, roads, rivers, fields and railways based on their shape. There is a considerable body of published work on the identification and classification of objects within images. Recognition is based on the matching of descriptions of shape. Several techniques have proved useful such as boundary chain encoding and moment invariants. The technique used here uses Fourier Descriptors. Based on a Fourier analysis technique applied to the boundary coÂordinates of an object expressed as complex numbers, Fourier descriptors are widely used in image processing to describe and classify shapes. The shape descriptors generated from the Fourier coefficients numerically describe shapes and can be normalised to make them independent of translation, scale and rotation. Cla...
http://eprints.nuim.ie/66/
Marked
Mark
Video semantic content analysis based on ontology
(2007)
Bai, Liang; Lao, Songyang; Jones, Gareth J.F.; Smeaton, Alan F.
Video semantic content analysis based on ontology
(2007)
Bai, Liang; Lao, Songyang; Jones, Gareth J.F.; Smeaton, Alan F.
Abstract:
The rapid increase in the available amount of video data is creating a growing demand for efficient methods for understanding and managing it at the semantic level. New multimedia standards, such as MPEG-4 and MPEG-7, provide the basic functionalities in order to manipulate and transmit objects and metadata. But importantly, most of the content of video data at a semantic level is out of the scope of the standards. In this paper, a video semantic content analysis framework based on ontology is presented. Domain ontology is used to define high level semantic concepts and their relations in the context of the examined domain. And low-level features (e.g. visual and aural) and video content analysis algorithms are integrated into the ontology to enrich video semantic analysis. OWL is used for the ontology description. Rules in Description Logic are defined to describe how features and algorithms for video analysis should be applied according to different perception content and low-leve...
http://doras.dcu.ie/218/
Marked
Mark
Facial feature extraction and principal component analysis for face detection in color images
(2004)
Cooray, Saman H.; O'Connor, Noel E.
Facial feature extraction and principal component analysis for face detection in color images
(2004)
Cooray, Saman H.; O'Connor, Noel E.
Abstract:
A hybrid technique based on facial feature extraction and Principal Component Analysis (PCA) is presented for frontal face detection in color images. Facial features such as eyes and mouth are automatically detected based on properties of the associated image regions, which are extracted by RSST color segmentation. While mouth feature points are identified using the redness property of regions, a simple search strategy relative to the position of the mouth is carried out to identify eye feature points from a set of regions. Priority is given to regions which signal high intensity variance, thereby allowing the most probable eye regions to be selected. On detecting a mouth and two eyes, a face verification step based on Eigenface theory is applied to a normalized search space in the image relative to the distance between the eye feature points.
http://doras.dcu.ie/285/
Marked
Mark
Enhancing person annotation for personal photo management using content and context based technologies
(2008)
Cooray, Saman H.
Enhancing person annotation for personal photo management using content and context based technologies
(2008)
Cooray, Saman H.
Abstract:
Rapid technological growth and the decreasing cost of photo capture means that we are all taking more digital photographs than ever before. However, lack of technology for automatically organising personal photo archives has resulted in many users left with poorly annotated photos, causing them great frustration when such photo collections are to be browsed or searched at a later time. As a result, there has recently been significant research interest in technologies for supporting effective annotation. This thesis addresses an important sub-problem of the broad annotation problem, namely "person annotation" associated with personal digital photo management. Solutions to this problem are provided using content analysis tools in combination with context data within the experimental photo management framework, called “MediAssist”. Readily available image metadata, such as location and date/time, are captured from digital cameras with in-built GPS functionality, and thus pro...
http://doras.dcu.ie/594/
Marked
Mark
MyPlaces: detecting important settings in a visual diary
(2008)
Blighe, Michael; O'Connor, Noel E.
MyPlaces: detecting important settings in a visual diary
(2008)
Blighe, Michael; O'Connor, Noel E.
Abstract:
We describe a novel approach to identifying specific settings in large collections of passively captured images corresponding to a visual diary. An algorithm developed for setting detection should be capable of detecting images captured at the same real world locations (e.g. in the dining room at home, in front of the computer in the office, in the park, etc.). This requires the selection and implementation of suitable methods to identify visually similar backgrounds in images using their visual features. We use a Bag of Keypoints approach. This method is based on the sampling and subsequent vector quantization of multiple image patches. The image patches are sampled and described using Scale Invariant Feature Transform (SIFT) features. We compare two different classifiers, K Nearest Neighbour and Multiclass Linear Perceptron, and present results for classifying ten different settings across one week’s worth of images. Our results demonstrate that the method produces good classifica...
http://doras.dcu.ie/641/
Marked
Mark
Video shot boundary detection: seven years of TRECVid activity
(2010)
Smeaton, Alan F.; Over, Paul; Doherty, Aiden R.
Video shot boundary detection: seven years of TRECVid activity
(2010)
Smeaton, Alan F.; Over, Paul; Doherty, Aiden R.
Abstract:
Shot boundary detection (SBD) is the process of automatically detecting the boundaries between shots in video. It is a problem which has attracted much attention since video became available in digital form as it is an essential pre-processing step to almost all video analysis, indexing, summarisation, search, and other content-based operations. Automatic SBD was one of the tracks of activity within the annual TRECVid benchmarking exercise, each year from 2001 to 2007 inclusive. Over those seven years we have seen 57 different research groups from across the world work to determine the best approaches to SBD while using a common dataset and common scoring metrics. In this paper we present an overview of the TRECVid shot boundary detection task, a high-level overview of the most significant of the approaches taken, and a comparison of performances, focussing on one year (2005) as an example.
http://doras.dcu.ie/4080/
Marked
Mark
Providing effective memory retrieval cues through automatic structuring and augmentation of a lifelog of images
(2009)
Doherty, Aiden R.
Providing effective memory retrieval cues through automatic structuring and augmentation of a lifelog of images
(2009)
Doherty, Aiden R.
Abstract:
Lifelogging is an area of research which is concerned with the capture of many aspects of an individual's life digitally, and within this rapidly emerging field is the significant challenge of managing images passively captured by an individual of their daily life. Possible applications vary from helping those with neurodegenerative conditions recall events from memory, to the maintenance and augmentation of extensive image collections of a tourist's trips. However, a large lifelog of images can quickly amass, with an average of 700,000 images captured each year, using a device such as the SenseCam. We address the problem of managing this vast collection of personal images by investigating automatic techniques that: 1. Identify distinct events within a full day of lifelog images (which typically consists of 2,000 images) e.g. breakfast, working on PC, meeting, etc. 2. Find similar events to a given event in a person's lifelog e.g. "show me other events where I wa...
http://doras.dcu.ie/2270/
Marked
Mark
A machine vision system for forensic analysis
(2005)
Ghita, Ovidiu; Gapert, René; Monks, Laura; Last, Jason; Whelan, Paul F.
A machine vision system for forensic analysis
(2005)
Ghita, Ovidiu; Gapert, René; Monks, Laura; Last, Jason; Whelan, Paul F.
Abstract:
Human skeletal remains are analysed by forensic anthropologists in order to draw conclusions about the probable identity of the deceased. During the analysis, the skull is used, along with other bones, to help determine the identity of the decedent. If only the base of the skull is available, forensic researchers take manual measurements from the large oval aperture in this region, the foramen magnum, in order to obtain information about the gender of the deceased. As this operation requires human intervention, the measurements are affected by the bias introduced by the human operator. The aim of this paper is to describe a full machine vision solution to perform precise morphological measurements of the foramen magnum. The system has been designed to extract measurements from 2D and 3D data and the returned results accurately match the manual measurements.
http://doras.dcu.ie/4644/
Marked
Mark
A vision-based system for inspecting painted slates
(2006)
Ghita, Ovidiu; Carew, Tim; Whelan, Paul F.
A vision-based system for inspecting painted slates
(2006)
Ghita, Ovidiu; Carew, Tim; Whelan, Paul F.
Abstract:
Purpose – This paper describes the development of a novel automated vision system used to detect the visual defects on painted slates. Design/methodology/approach – The vision system that has been developed consists of two major components covering the opto-mechanical and algorithmical aspects of the system. The first component addresses issues including the mechanical implementation and interfacing the inspection system with the development of a fast image processing procedure able to identify visual defects present on the slate surface. Findings – The inspection system was developed on 400 slates to determine the threshold settings that give the best trade-off between no false positive triggers and correct defect identification. The developed system was tested on more than 300 fresh slates and the success rate for correct identification of acceptable and defective slates was 99.32 per cent for defect free slates based on 148 samples and 96.91 per cent for defective slates based ...
http://doras.dcu.ie/4681/
Marked
Mark
Musical instrument identification using principal componant analysis and multi-layered perceptions
(2009)
Loughran, Roisin; Walker, Jacqueline; O'Neill, Michael; O'Farrell, Marion
Musical instrument identification using principal componant analysis and multi-layered perceptions
(2009)
Loughran, Roisin; Walker, Jacqueline; O'Neill, Michael; O'Farrell, Marion
Abstract:
Presented at the International Conference on Audio, Language and Image Processing (ICALIP), 7-9 July 2008, Shanghai, China.
SFI
http://hdl.handle.net/10344/142
Marked
Mark
Content-based image descriptors for enhanced person annotation in personal digital photo archives
(2009)
Cooray, Saman H.; O'Connor, Noel E.
Content-based image descriptors for enhanced person annotation in personal digital photo archives
(2009)
Cooray, Saman H.; O'Connor, Noel E.
Abstract:
In this paper we investigate the use of content-based image descriptors for enhancing the performance of person annotation in personal photo management applications. The descriptors examined are related to the context of person recognition through face and body-patch feature matching in personal digital photos. In order to identify the best performing content-based descriptors, we first study a number of colour and texture descriptors for body-patch matching and face recognition descriptors for face matching using a suitably chosen data set taken from typical personal photo collections. We then analyse the performance of three different fusion schemes to identify the best combination of colour, texture and face recognition descriptors. Finally, we apply those descriptors to the problem of person annotation and measure their performance using a test data set, which comprises 7 different real-life personal photo collections. The experimental results illustrate that combining bodypatch...
http://doras.dcu.ie/14916/
Marked
Mark
Short-term rainfall nowcasting: using rainfall radar imaging
(2009)
Wang, Peng; Smeaton, Alan F.; Songyang, Lao; O'Connor, Edel; Ling, Yunxiang; O...
Short-term rainfall nowcasting: using rainfall radar imaging
(2009)
Wang, Peng; Smeaton, Alan F.; Songyang, Lao; O'Connor, Edel; Ling, Yunxiang; O'Connor, Noel E.
Abstract:
As one of the most useful sources of quantitative precipitation measurement, rainfall radar analysis can be a very useful focus for research into developing methods for rainfall prediction. Because radar can estimate rainfall distribution over a wide range, it is thus very attractive for weather prediction over a large area. Short lead time rainfall prediction is often needed in meteorological and hydrological applications where accurate prediction of rainfall can help with flood relief, with agriculture and with event planning. A system of short-term rainfall prediction over Ireland using rainfall radar image processing is presented in this paper. As the only input, consecutive rainfall radar images are processed to predict the development of rainfall by means of morphological methods and movement extrapolation. The results of a series of experimental evaluations demonstrate the ability and efficiency of using our rainfall radar imaging in a nowcasting system.
http://doras.dcu.ie/15029/
Marked
Mark
Double Markov random fields and Bayesian image segmentation
(2002)
WILSON, SIMON PAUL
Double Markov random fields and Bayesian image segmentation
(2002)
WILSON, SIMON PAUL
Abstract:
peer-reviewed
Markov random fields are used extensively in modelbased approaches to image segmentation and, under the Bayesian paradigm, are implemented through Markov chain Monte Carlo (MCMC) methods. In this paper,we describe a class of such models (the double Markov random field) for images composed of several textures, which we consider to be the natural hierarchical model for such a task.We show how several of the Bayesian approaches in the literature can be viewed as modifications of this model, made in order to make MCMC implementation possible. From a simulation study, conclusions are made concerning the performance of these modified models.
http://hdl.handle.net/2262/32972
Marked
Mark
Estimating 3D Scene Flow from Multiple 2D Optical Flows
(2009)
DAHYOT, ROZENN; MANZKE, MICHAEL; RUTTLE, JONATHAN LEONARD
Estimating 3D Scene Flow from Multiple 2D Optical Flows
(2009)
DAHYOT, ROZENN; MANZKE, MICHAEL; RUTTLE, JONATHAN LEONARD
Abstract:
peer-reviewed
http://hdl.handle.net/2262/30634
Marked
Mark
Feature-based object modelling for visual surveillance
(2008)
BAUGH, GARY; KOKARAM, ANIL CHRISTOPHER
Feature-based object modelling for visual surveillance
(2008)
BAUGH, GARY; KOKARAM, ANIL CHRISTOPHER
http://hdl.handle.net/2262/27640
Marked
Mark
Implicit spatial inference with sparse local features
(2008)
KOKARAM, ANIL CHRISTOPHER; O'REGAN, DEIRDRE
Implicit spatial inference with sparse local features
(2008)
KOKARAM, ANIL CHRISTOPHER; O'REGAN, DEIRDRE
http://hdl.handle.net/2262/27639
Marked
Mark
Unsupervised Camera Motion Estimation and Moving Object Detection in Videos
(2006)
DAHYOT, ROZENN
Unsupervised Camera Motion Estimation and Moving Object Detection in Videos
(2006)
DAHYOT, ROZENN
Abstract:
In this article, we consider the robust estimation of a location parameter using Mestimators. We propose here to couple this estimation with the robust scale estimate proposed in [Dahyot and Wilson, 2006]. The resulting procedure is then completely unsupervised. It is applied to camera motion estimation and moving object detection in videos. Experimental results on different video materials show the adaptability and the accuracy of this new robust approach.
http://hdl.handle.net/2262/2058
Marked
Mark
Classification and representation of semantic content in broadcast tennis videos
(2005)
KOKARAM, ANIL CHRISTOPHER
Classification and representation of semantic content in broadcast tennis videos
(2005)
KOKARAM, ANIL CHRISTOPHER
Abstract:
peer-reviewed
This paper investigates the semantic analysis of broadcast tennis footage. We consider the spatio-temporal behaviour of an object in the footage as being the embodiment of a semantic event. This object is tracked using a colour based particle filter. The video syntax and audio features are used to help delineate the temporal boundaries of these events. For broadcast tennis footage, the system firstly parses the video sequence based on the geometry of the content in view and classifies the clip as a particular view type. The temporal behaviour of the serving player is modelled using a HMM. As a result, each model is representative of a particular semantic episode. Events are then summarised using a number of synthesised keyframes.
http://hdl.handle.net/2262/19779
Marked
Mark
Cellular tracking in time-lapse phase contrast images
(2009)
Thirusittampalam, K.; Hossain, Mohammad J.; Ghita, Ovidiu; Whelan, Paul F.
Cellular tracking in time-lapse phase contrast images
(2009)
Thirusittampalam, K.; Hossain, Mohammad J.; Ghita, Ovidiu; Whelan, Paul F.
Abstract:
The quantitative analysis of live cells is a key issue in evaluating biological processes. The current clinical practice involves the application of a tedious and time consuming manual tracking procedure on large amount of data. As a result, automatic tracking systems are currently developed and evaluated. However, problems caused by cellular division, agglomeration, Brownian motion and topology changes are difficult issues that have to be accommodated by automatic tracking techniques. In this paper, we detail the development of a fully automated multi-target tracking system that is able to deal with Brownian motion and cellular division. During the tracking process our approach includes the neighbourhood relationship and motion history to enforce the cellular tracking continuity in the spatial and temporal domain. The experimental results reported in this paper indicate that our method is able to accurately track cellular structures in time-lapse data.
http://doras.dcu.ie/15571/
Marked
Mark
Cost-effective HPC clustering for computer vision applications
(2008)
Dietlmeier, Julia; Begley, Seán; Whelan, Paul F.
Cost-effective HPC clustering for computer vision applications
(2008)
Dietlmeier, Julia; Begley, Seán; Whelan, Paul F.
Abstract:
We will present a cost-effective and flexible realization of high performance computing (HPC) clustering and its potential in solving computationally intensive problems in computer vision. The featured software foundation to support the parallel programming is the GNU parallel Knoppix package with message passing interface (MPI) based Octave, Python and C interface capabilities. The implementation is especially of interest in applications where the main objective is to reuse the existing hardware infrastructure and to maintain the overall budget cost. We will present the benchmark results and compare and contrast the performances of Octave and MATLAB.
http://doras.dcu.ie/15574/
Marked
Mark
Digital image correlation and finite element modelling as a method to determine mechanical properties of human soft tissue in vivo.
(2009)
SIMMS, CIARAN KNUT; MOERMAN, KEVIN MATTHEUS
Digital image correlation and finite element modelling as a method to determine mechanical properties of human soft tissue in vivo.
(2009)
SIMMS, CIARAN KNUT; MOERMAN, KEVIN MATTHEUS
Abstract:
The mechanical properties of human soft tissue are crucial for impact biomechanics, rehabilitation engineering and surgical simulation. Validation of these constitutive models using human data remains challenging and often requires the use of non-invasive imaging and inverse finite element (FE) analysis. Post processing data from imaging methods such as tagged magnetic resonance imaging (MRI) can be challenging. Digital Image Correlation (DIC) however is a relatively straightforward imaging method and thus the goal of this study was to assess the use of DIC in combination with FE modelling to determine the bulk material properties of human soft tissue. Indentation experiments were performed on a silicone gel soft tissue phantom. A two camera DIC setup was then used to record the 3D surface deformation. The experiment was then simulated using a FE model. The gel was modelled as Neo-Hookean hyperelastic and the material parameters were determined by minimising the error between the ex...
http://hdl.handle.net/2262/41171
Marked
Mark
Using wearable image sensing to measure physical activity & sedentary behavior
(2011)
Doherty, Aiden R.
Using wearable image sensing to measure physical activity & sedentary behavior
(2011)
Doherty, Aiden R.
Abstract:
This presentation will be of interest to 1) physical activity researchers interested in better capturing participant physical activity and sedentary behaviour, and 2) computer science researchers interested in wearable sensors and image processing challenges in a new application area. In this lecture, Dr Doherty will discuss use of the Microsoft Research SenseCam, a wearable camera sensor which automatically captures up to 5,000 first-person point-of-view images. The images strongly help identify the type of activity a participant is involved in, and can also help determine the environment and situation surrounding the given activity. Because up to 35,000 images can be captured from a participant each week, there exists a substantial information management challenge in storing, annotating, and retrieving image content. This talk will discuss current state-of-art computational approaches applied to SenseCam images, and their application in the field of physical activity.
http://doras.dcu.ie/16294/
Marked
Mark
Dynamic voxel carving in tennis based on player localisation using a low cost camera network
(2011)
Monaghan, David; Kelly, Philip; O'Connor, Noel E.
Dynamic voxel carving in tennis based on player localisation using a low cost camera network
(2011)
Monaghan, David; Kelly, Philip; O'Connor, Noel E.
Abstract:
In this paper, we address the problem of reconstructing 3D volumetric models, illustrating human sporting performance for use in coaching scenarios. We advocate the use of low cost camera networks for acquiring such data, allowing the approach to be feasibly adopted by both amateur and elite level sports athletes. A dynamic voxel carving approach is described, coupled with over-head player tracking and autonomous background subtraction, to automatically produce a 3D reconstruction technique that intelligently uses memory resources. We demonstrate the efficacy of our approach in the context of tennis as a challenging application scenario.
http://doras.dcu.ie/16322/
Displaying Results 76 - 100 of 366 on page 4 of 15
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