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Author = O'Connor, Noel E.;
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Displaying Results 1 - 25 of 490 on page 1 of 20
Marked
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3D estimation and visualization of motion in a multicamera network for sports
(2011)
Kelly, Philip; O'Connor, Noel E.
3D estimation and visualization of motion in a multicamera network for sports
(2011)
Kelly, Philip; O'Connor, Noel E.
Abstract:
In this work, we develop image processing and computer vision techniques for visually tracking a tennis ball, in 3D, on a court instrumented with multiple low cost IP cameras. The technique first extracts 2D ball track data from each camera view, using object tracking methods. Next, an automatic feature- based video synchronization method is applied. This technique uses both the extracted 2D ball information from two or more camera views, plus camera calibration information. Then, in order to find 3D trajectory, the temporal 3D locations of the ball is estimated using triangulation of correspondent 2D locations obtained from automatically synchronized videos. Furthermore, we also incorporate a physics-based trajectory model into the system to improve the continuity of the tracked 3D ball during times when no two cameras have overlapping views of the ball location. The resultant 3D ball tracks are then visualized in a virtual 3D graphical environment. Finally, we quantify the accurac...
http://doras.dcu.ie/16575/
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3D image analysis for pedestrian detection
(2006)
Kelly, Philip; Cooke, Eddie; O'Connor, Noel E.; Smeaton, Alan F.
3D image analysis for pedestrian detection
(2006)
Kelly, Philip; Cooke, Eddie; O'Connor, Noel E.; Smeaton, Alan F.
Abstract:
A method for solving the dense disparity stereo correspondence problem is presented in this paper. This technique is designed specifically for pedestrian detection type applications. A new Ground Control Points (GCPs) scheme is introduced, using groundplane homography information to determine regions in which good GCPs are likely to occur. The method also introduces a dynamic disparity limit constraint to further improve GCP selection and dense disparity generation. The technique is applied to a real world pedestrian detection scenario with a background modeling system based on disparity and edges.
http://doras.dcu.ie/381/
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3DSAL: an efficient 3D-CNN architecture for video saliency prediction
(2020)
Djilali, Yasser Abdelaziz Dahou; Sayah, Mohamed; McGuinness, Kevin; O'Connor, Noel E.
3DSAL: an efficient 3D-CNN architecture for video saliency prediction
(2020)
Djilali, Yasser Abdelaziz Dahou; Sayah, Mohamed; McGuinness, Kevin; O'Connor, Noel E.
Abstract:
In this paper, we propose a novel 3D CNN architecture that enables us to train an effective video saliency prediction model. The model is designed to capture important motion information using multiple adjacent frames. Our model performs a cubic convolution on a set of consecutive frames to extract spatio-temporal fea- tures. This enables us to predict the saliency map for any given frame using past frames. We comprehensively investigate the performance of our model with respect to state-of-the-art video saliency models. Experimental results on three large-scale datasets, DHF1K, UCF-SPORTS and DAVIS, demonstrate the competitiveness of our approach.
http://doras.dcu.ie/24019/
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A collaborative approach to video summarization
(2008)
Dumont, Emilie; Merialdo, Bernard; Essid, Slim; Bailer, Werner; Byrne, Daragh; Bredin, ...
A collaborative approach to video summarization
(2008)
Dumont, Emilie; Merialdo, Bernard; Essid, Slim; Bailer, Werner; Byrne, Daragh; Bredin, Hervé; O'Connor, Noel E.; Jones, Gareth J.F.; Haller, Martin; Krutz, Andreas; Sikora, Thomas; Piatrik, Tomas
Abstract:
This poster describes an approach to video summarization based on the combination of several decision mechanisms provided by the partners of the KSpace European Network of Excellence. The system has been applied to the TRECVID 2008 BBC rushes summarization task.
http://doras.dcu.ie/16510/
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A combined audio-visual contribution to event detection in field sports broadcast video. Case study: Gaelic football
(2003)
Sadlier, David A.; O'Connor, Noel E.; Marlow, Seán; Murphy, Noel
A combined audio-visual contribution to event detection in field sports broadcast video. Case study: Gaelic football
(2003)
Sadlier, David A.; O'Connor, Noel E.; Marlow, Seán; Murphy, Noel
Abstract:
In this paper we propose novel, audio-visual analysis techniques for event detection in broadcast TV sports video content. The scope of the design is constrained to the specialized domain of 'field sport', and specifically, Gaelic Football is presented as an experimental case study. We show that a combination of speech-band energy tracking in the audio domain, coupled with colour dominance pattern recognition in the video domain, provides a useful contribution to event detection for broadcast Gaelic Football matches. It is projected that, any conclusions made therein may be extended such that they function on sports content of a similar nature such as American Football, Australian Rules, Rugby Union etc.
http://doras.dcu.ie/244/
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A comparative evaluation of interactive segmentation algorithms
(2010)
McGuinness, Kevin; O'Connor, Noel E.
A comparative evaluation of interactive segmentation algorithms
(2010)
McGuinness, Kevin; O'Connor, Noel E.
Abstract:
In this paper we present a comparative evaluation of four popular interactive segmentation algorithms. The evaluation was carried out as a series of user-experiments, in which participants were tasked with extracting 100 objects from a common dataset: 25 with each algorithm, constrained within a time limit of 2 min for each object. To facilitate the experiments, a “scribble-driven” segmentation tool was developed to enable interactive image segmentation by simply marking areas of foreground and background with the mouse. As the participants refined and improved their respective segmentations, the corresponding updated segmentation mask was stored along with the elapsed time. We then collected and evaluated each recorded mask against a manually segmented ground truth, thus allowing us to gauge segmentation accuracy over time. Two benchmarks were used for the evaluation: the well-known Jaccard index for measuring object accuracy, and a new fuzzy metric, proposed in this paper, designe...
http://doras.dcu.ie/14846/
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A comparison between end-to-end approaches and feature extraction based approaches for Sign Language recognition
(2018)
Oliveira, Marlon; Chatbri, Houssem; Little, Suzanne; O'Connor, Noel E.; Sutherland...
A comparison between end-to-end approaches and feature extraction based approaches for Sign Language recognition
(2018)
Oliveira, Marlon; Chatbri, Houssem; Little, Suzanne; O'Connor, Noel E.; Sutherland, Alistair
Abstract:
In this work we use a new image dataset for Irish Sign Language (ISL) and we compare different approaches for recognition. We perform experiments and report comparative accuracy and timing. We perform tests over blurred images and compare results with non-blurred images. For classification, we use end-to-end approach, such as Convolutional Neural Networks (CNN) and feature based extraction approaches, such as Principal Component Analysis (PCA) followed by different classifiers, i.e. multilayer perceptron (MLP). We obtain a recognition accuracy over 99% for both approaches. In addition, we report different ways to split the training and testing dataset, being one iterative and the other one random selected.
http://doras.dcu.ie/22132/
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A content-based retrieval system for UAV-like video and associated metadata
(2008)
O'Connor, Noel E.; Duffy, Thomas; Gurrin, Cathal; Lee, Hyowon; Sadlier, David A.; ...
A content-based retrieval system for UAV-like video and associated metadata
(2008)
O'Connor, Noel E.; Duffy, Thomas; Gurrin, Cathal; Lee, Hyowon; Sadlier, David A.; Smeaton, Alan F.; Zhang, Ke
Abstract:
In this paper we provide an overview of a content-based retrieval (CBR) system that has been specifically designed for handling UAV video and associated meta-data. Our emphasis in designing this system is on managing large quantities of such information and providing intuitive and efficient access mechanisms to this content, rather than on analysis of the video content. The retrieval unit in our system is termed a "trip". At capture time, each trip consists of an MPEG-1 video stream and a set of time stamped GPS locations. An analysis process automatically selects and associates GPS locations with the video timeline. The indexed trip is then stored in a shared trip repository. The repository forms the backend of a MPEG-211 compliant Web 2.0 application for subsequent querying, browsing, annotation and video playback. The system interface allows users to search/browse across the entire archive of trips and, depending on their access rights, to annotate other users' tri...
http://doras.dcu.ie/2449/
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A Dataset for Irish sign language recognition
(2017)
Oliveira, Marlon; Chatbri, Houssem; Ferstl, Ylva; Farouk, Mohamed; Little, Suzanne; O...
A Dataset for Irish sign language recognition
(2017)
Oliveira, Marlon; Chatbri, Houssem; Ferstl, Ylva; Farouk, Mohamed; Little, Suzanne; O'Connor, Noel E.; Sutherland, Alistair
Abstract:
We introduce a new image dataset for Irish Sign Language (ISL) recognition. We filmed human subjects performing ISL hand-shapes and movements, resulting in 468 videos. Then, we extracted frames from the videos. This resulted in a total of 58,114 images for the 23 common hand-shapes from the ISL language. This dataset is a part of our ongoing work on ISL recognition using pattern recognition methods. In addition to the dataset, we report experiments using Principal Component Analysis (PCA) where we reached 95% recognition accuracy.
http://doras.dcu.ie/21882/
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A deep residual architecture for skin lesion segmentation
(2018)
Gurram Munirathnam, Venkatesh; Yarlapati Ganesh, Naresh; Little, Suzanne; O'Connor...
A deep residual architecture for skin lesion segmentation
(2018)
Gurram Munirathnam, Venkatesh; Yarlapati Ganesh, Naresh; Little, Suzanne; O'Connor, Noel E.
Abstract:
In this paper, we propose an automatic approach to skin lesion region segmentation based on a deep learning architecture with multi-scale residual connections. The architecture of the proposed model is based on UNet [22] with residual connections to maximise the learning capability and performance of the network. The information lost in the encoder stages due to the max-pooling layer at each level is preserved through the multi-scale residual connections. To corroborate the efficacy of the proposed model, extensive experiments are conducted on the ISIC 2017 challenge dataset without using any external dermatologic image set. An extensive comparative analysis is presented with contemporary methodologies to highlight the promising performance of the proposed methodology.
http://doras.dcu.ie/22685/
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A Demonstration of the PATHway System for Technology-enabled Exercise-based Cardiac Rehabilitation
(2016)
Moran, Kieran; Wei, Haolin; Monaghan, David; Woods, Catherine; O'Connor, Noel E.; ...
A Demonstration of the PATHway System for Technology-enabled Exercise-based Cardiac Rehabilitation
(2016)
Moran, Kieran; Wei, Haolin; Monaghan, David; Woods, Catherine; O'Connor, Noel E.; Zarpalas, Dimitrios; Chatzitofis, Anargyros; Daras, Petros; Piesk, Jens; Pomazanskyi, Andrew
Abstract:
We described an invited demonstration to MMHealth’16 of a platform for technology-enabled exercise-based Cardiac Rehabilitation (CR). The demo focuses on one technical aspect of a much broader lifestyle intervention program i.e. realtime estimation of a user’s adherence to an exercise programm
http://doras.dcu.ie/21346/
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A flexible ensemble-SVM for computer vision tasks
(2016)
Trichet, Remi; O'Connor, Noel E.
A flexible ensemble-SVM for computer vision tasks
(2016)
Trichet, Remi; O'Connor, Noel E.
Abstract:
This paper presents an ensemble-SVM method that features a data selection mechanism with stochastic and deterministic properties, the use of extreme value theory for classifier calibration, and the introduction of random forest for classifier combination. We applied the proposed algorithm to 2 event recognition datasets and the PASCAL2007 object detection dataset and compared it to single SVM and common computer vision ensemble-SVM methods. Our algorithm outperforms its competitors and shows a considerable boost on datasets with a limited amount of outliers.
http://doras.dcu.ie/21326/
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A framework and user interface for automatic region based segmentation algorithms
(2006)
McGuinness, Kevin; Keenan, Gordon; Adamek, Tomasz; O'Connor, Noel E.
A framework and user interface for automatic region based segmentation algorithms
(2006)
McGuinness, Kevin; Keenan, Gordon; Adamek, Tomasz; O'Connor, Noel E.
Abstract:
In this paper we describe a framework and tool developed for running and evaluating automatic region based segmentation algorithms. The tool was designed to allow simple integration of existing and future segmentation algorithms, both single image based algorithms and those that operate on video data. Our framework supports plug-in segmenters, media decoders, and region-map codecs. We provide several sophisticated implementations of these plug-ins, including a video decoder capable of frame accurate decoding of a large variety of video formats, an image decoder which also handles a comprehensive collection of formats, and a efficient implementation of a region-map codec. The tool includes both a graphical user interface to allow users to browse, visually inspect, and evaluate the algorithm output, and a batch processing interface for segmentation of large data collections. The application allows researchers to focus more on the development and evaluation of segmentation methods, rel...
http://doras.dcu.ie/310/
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A framework for comprehensive analysis of a swing in sports using low-cost inertial sensors
(2014)
Ahmadi, Amin; Destelle, Francois; Monaghan, David; O'Connor, Noel E.; Richter, Chr...
A framework for comprehensive analysis of a swing in sports using low-cost inertial sensors
(2014)
Ahmadi, Amin; Destelle, Francois; Monaghan, David; O'Connor, Noel E.; Richter, Chris; Moran, Kieran
Abstract:
We present a novel framework to monitor the three- dimensional trajectory (orientation and position) of a golf swing using miniaturized inertial sensors. Firstly we employed a highly accurate and computationally efficient revised gradient descent algorithm to obtain the orientation of a golf club. Secondly, we designed a series of digital filters to determine the backward and forward segments of the swing, enabling us to calculate drift-free linear velocity along with the relative 3D position of the golf club during the entire swing. Finally, the calculated motion trajectory was verified against a ground truth VICON system using Iterative Closest Point (ICP) in conjunction with Principal Component Analysis (PCA). The computationally efficient framework present here achieves a high level of accuracy (r = 0.9885, p < 0.0001) for such a low-cost system. This framework can be utilized for reliable movement technique evaluation and can provide near real-time feedback for athletes in v...
http://doras.dcu.ie/20594/
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A framework for evaluating stereo-based pedestrian detection techniques
(2008)
Kelly, Philip; O'Connor, Noel E.; Smeaton, Alan F.
A framework for evaluating stereo-based pedestrian detection techniques
(2008)
Kelly, Philip; O'Connor, Noel E.; Smeaton, Alan F.
Abstract:
Automated pedestrian detection, counting, and tracking have received significant attention in the computer vision community of late. As such, a variety of techniques have been investigated using both traditional 2-D computer vision techniques and, more recently, 3-D stereo information. However, to date, a quantitative assessment of the performance of stereo-based pedestrian detection has been problematic, mainly due to the lack of standard stereo-based test data and an agreed methodology for carrying out the evaluation. This has forced researchers into making subjective comparisons between competing approaches. In this paper, we propose a framework for the quantitative evaluation of a short-baseline stereo-based pedestrian detection system. We provide freely available synthetic and real-world test data and recommend a set of evaluation metrics. This allows researchers to benchmark systems, not only with respect to other stereo-based approaches, but also with more traditional 2-D app...
http://doras.dcu.ie/652/
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A framework for event detection in field-sports video broadcasts based on SVM generated audio-visual feature model. Case-study: soccer video
(2004)
Sadlier, David A.; O'Connor, Noel E.; Murphy, Noel; Marlow, Seán
A framework for event detection in field-sports video broadcasts based on SVM generated audio-visual feature model. Case-study: soccer video
(2004)
Sadlier, David A.; O'Connor, Noel E.; Murphy, Noel; Marlow, Seán
Abstract:
In this paper we propose a novel audio-visual feature-based framework, for event detection in field sports broadcast video. The system is evaluated via a case-study involving MPEG encoded soccer video. Specifically, the evidence gathered by various feature detectors is combined by means of a learning algorithm (a support vector machine), which infers the occurrence of an event, based on a model generated during a training phase, utilizing a corpus of 25 hours of content. The system is evaluated using 25 hours of separate test content. Following an evaluation of results obtained, it is shown for this case, that both high precision and recall statistics are achievable.
http://doras.dcu.ie/399/
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A framework for human-like behavior in an immersive virtual world
(2013)
Kuijk, Fons; Van Broeck, Sigurd; Dareau, Claude; Ravenet, Brian; Ochs, Magalie; Apostol...
A framework for human-like behavior in an immersive virtual world
(2013)
Kuijk, Fons; Van Broeck, Sigurd; Dareau, Claude; Ravenet, Brian; Ochs, Magalie; Apostolakis, Konstantinos; Daras, Petros; Monaghan, David; O'Connor, Noel E.; Wall, Julie; Izquierdo, Ebroul
Abstract:
Just as readers feel immersed when the story-line adheres to their experiences, users will more easily feel immersed in a virtual environment if the behavior of the characters in that environment adheres to their expectations, based on their life-long observations in the real world. This paper introduces a framework that allows authors to establish natural, human-like behavior, physical interaction and emotional engagement of characters living in a virtual environment. Represented by realistic virtual characters, this framework allows people to feel immersed in an Internet based virtual world in which they can meet and share experiences in a natural way as they can meet and share experiences in real life. Rather than just being visualized in a 3D space, the virtual characters (autonomous agents as well as avatars representing users) in the immersive environment facilitate social interaction and multi-party collaboration, mixing virtual with real.
http://doras.dcu.ie/18089/
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A framework for realistic 3D tele-immersion
(2013)
Fechteler, P.; Hilsmann, Andreas; Brock, S.V.; Stevens, C.; Wall, Julie; Sanna, M.; Mau...
A framework for realistic 3D tele-immersion
(2013)
Fechteler, P.; Hilsmann, Andreas; Brock, S.V.; Stevens, C.; Wall, Julie; Sanna, M.; Mauro, D.A.; Kuijk, Fons; Mekuria, Rufael; Cesar, P.; Monaghan, David; O'Connor, Noel E.; Daras, Petros; Alexiadis, D.S.; Zahariadis, T.
Abstract:
Meeting, socializing and conversing online with a group of people using teleconferencing systems is still quite differ- ent from the experience of meeting face to face. We are abruptly aware that we are online and that the people we are engaging with are not in close proximity. Analogous to how talking on the telephone does not replicate the experi- ence of talking in person. Several causes for these differences have been identified and we propose inspiring and innova- tive solutions to these hurdles in attempt to provide a more realistic, believable and engaging online conversational expe- rience. We present the distributed and scalable framework REVERIE that provides a balanced mix of these solutions. Applications build on top of the REVERIE framework will be able to provide interactive, immersive, photo-realistic ex- periences to a multitude of users that for them will feel much more similar to having face to face meetings than the expe- rience offered by conventional teleconfere...
http://doras.dcu.ie/18171/
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A generic news story segmentation system and its evaluation
(2004)
O'Hare, Neil; Smeaton, Alan F.; Czirjék, Csaba; O'Connor, Noel E.; Murphy, Noel
A generic news story segmentation system and its evaluation
(2004)
O'Hare, Neil; Smeaton, Alan F.; Czirjék, Csaba; O'Connor, Noel E.; Murphy, Noel
Abstract:
The paper presents an approach to segmenting broadcast TV news programmes automatically into individual news stories. We first segment the programme into individual shots, and then a number of analysis tools are run on the programme to extract features to represent each shot. The results of these feature extraction tools are then combined using a support vector machine trained to detect anchorperson shots. A news broadcast can then be segmented into individual stories based on the location of the anchorperson shots within the programme. We use one generic system to segment programmes from two different broadcasters, illustrating the robustness of our feature extraction process to the production styles of different broadcasters.
http://doras.dcu.ie/242/
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A hybrid method for indoor user localisation
(2009)
Redzic, Milan; Ó Conaire, Ciarán; Brennan, Conor; O'Connor, Noel E.
A hybrid method for indoor user localisation
(2009)
Redzic, Milan; Ó Conaire, Ciarán; Brennan, Conor; O'Connor, Noel E.
Abstract:
In this work we describe an approach to indoor user localisation by combining image-based and RF-based methods and compare this new approach to prior work. This paper details a new algorithm for indoor user localisation, demonstrating more effective user localisation than prior approaches and therefore presents the next step in combining two different technologies for localisation in indoor type environments.
http://doras.dcu.ie/14798/
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A hybrid technique for face detection in color images
(2005)
Cooray, Saman H.; O'Connor, Noel E.
A hybrid technique for face detection in color images
(2005)
Cooray, Saman H.; O'Connor, Noel E.
Abstract:
In this paper, a hybrid technique for face detection in color images is presented. The proposed technique combines three analysis models, namely skin detection, automatic eye localization, and appearance-based face/nonface classification. Using a robust histogram-based skin detection model, skin-like pixels are first identified in the RGB color space. Based on this, face bounding-boxes are extracted from the image. On detecting a face bounding-box, approximate positions of the candidate mouth feature points are identified using the redness property of image pixels. A region-based eye localization step, based on the detected mouth feature points, is then applied to face bounding-boxes to locate possible eye feature points in the image. Based on the distance between the detected eye feature points, face/non-face classification is performed over a normalized search area using the Bayesian discriminating feature (BDF) analysis method. Some subjective evaluation results are presented on ...
http://doras.dcu.ie/235/
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A lifelogging approach to automated market research
(2012)
Hughes, Mark; Newman, Eamonn; Smeaton, Alan F.; O'Connor, Noel E.
A lifelogging approach to automated market research
(2012)
Hughes, Mark; Newman, Eamonn; Smeaton, Alan F.; O'Connor, Noel E.
Abstract:
Market research companies spend large amounts of money carrying out time-intensive processes to gather information about peo- ple’s activities, such as the place they frequent and the activities in which they partake. Due to high costs and logistical difficulties, an automated approach to this practice is needed. In this work we present an automated market research system based on computer vision and machine learning algorithms with visual lifelogging data, developed in collaboration with Sponge It, a market research com- pany. Due to some image quality constraints associated with the Sense- cam, for our prototype system we developed a visual lifelogging device using an Android smartphone. This device can capture images at higher resolutions and with additional metadata, such as location information. The aim of this project is to analyse large collections of visual lifelogs and to support both ethnographic research and audience measurement for market research. Ethnographic research ...
http://doras.dcu.ie/17140/
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A low complexity hardware architecture for motion estimation
(2006)
Larkin, Daniel; Muresan, Valentin; O'Connor, Noel E.
A low complexity hardware architecture for motion estimation
(2006)
Larkin, Daniel; Muresan, Valentin; O'Connor, Noel E.
Abstract:
This paper tackles the problem of accelerating motion estimation for video processing. A novel architecture using binary data is proposed, which attempts to reduce power consumption. The solution exploits redundant operations in the sum of absolute differences (SAD) calculation, by a mechanism known as early termination. Further data redundancies are exploited by using a run length coding addressing scheme, where access to pixels which do not contribute to the final SAD value is minimised. By using these two techniques operations and memory accesses are reduced by 93.29% and 69.17% respectively relative to a systolic array implementation.
http://doras.dcu.ie/229/
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A low-cost head and eye tracking system for realistic eye movements in virtual avatars
(2014)
Li, Yingbo; Wei, Haolin; Monaghan, David; O'Connor, Noel E.
A low-cost head and eye tracking system for realistic eye movements in virtual avatars
(2014)
Li, Yingbo; Wei, Haolin; Monaghan, David; O'Connor, Noel E.
Abstract:
A virtual avatar or autonomous agent is a digital representation of a human being that can be controlled by either a human or an artificially intelligent computer system. Increasingly avatars are becoming realistic virtual human characters that exhibit human behavioral traits, body language and eye and head movements. As the interpretation of eye and head movements represents an important part of nonverbal human communication it is extremely important to accurately reproduce these movements in virtual avatars to avoid falling into the well-known ``uncanny valley''. In this paper we present a cheap hybrid real-time head and eye tracking system based on existing open source software and commonly available hardware. Our evaluation indicates that the system of head and eye tracking is stable and accurate and can allow a human user to robustly puppet a virtual avatar, potentially allowing us to train an A.I. system to learn realistic human head and eye movements.
http://doras.dcu.ie/19587/
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A low-cost smart sensor network for catchment monitoring
(2019)
Zhang, Dian; Heery, Brendan; O’Neil, Maria; Little, Suzanne; O'Connor, Noel E.; Re...
A low-cost smart sensor network for catchment monitoring
(2019)
Zhang, Dian; Heery, Brendan; O’Neil, Maria; Little, Suzanne; O'Connor, Noel E.; Regan, Fiona
Abstract:
Understanding hydrological processes in large, open areas, such as catchments, and further modelling these processes are still open research questions. The system proposed in this work provides an automatic end-to-end pipeline from data collection to information extraction that can potentially assist hydrologists to better understand the hydrological processes using a data-driven approach. In this work, the performance of a low-cost off-the-shelf self contained sensor unit, which was originally designed and used to monitor liquid levels, such as AdBlue, fuel, lubricants etc., in a sealed tank environment, is first examined. This process validates that the sensor does provide accurate water level information for open water level monitoring tasks. Utilising the dataset collected from eight sensor units, an end-to-end pipeline of automating the data collection, data processing and information extraction processes is proposed. Within the pipeline, a data-driven anomaly detection method ...
http://doras.dcu.ie/23783/
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