Search

Your search keyword '"Nikolov, Ivan"' showing total 261 results
Start Over Author "Nikolov, Ivan"
261 results on '"Nikolov, Ivan"'

1. BrackishMOT: The Brackish Multi-Object Tracking Dataset

Author

Pedersen, Malte, Lehotský, Daniel, Nikolov, Ivan, and Moeslund, Thomas B.

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

There exist no publicly available annotated underwater multi-object tracking (MOT) datasets captured in turbid environments. To remedy this we propose the BrackishMOT dataset with focus on tracking schools of small fish, which is a notoriously difficult MOT task. BrackishMOT consists of 98 sequences captured in the wild. Alongside the novel dataset, we present baseline results by training a state-of-the-art tracker. Additionally, we propose a framework for creating synthetic sequences in order to expand the dataset. The framework consists of animated fish models and realistic underwater environments. We analyse the effects of including synthetic data during training and show that a combination of real and synthetic underwater training data can enhance tracking performance. Links to code and data can be found at https://www.vap.aau.dk/brackishmot

Published
2023

3. Building Teamwork: Mixed Reality Game for Developing Trust and Communication

Author

Jespersen, Kristian, Julsgaard, Kristian, Madsbøll, Jens Lakmann, Niebuhr, Mathias Øgaard, Lundbak, Marcus Høyen, Odgaard, Rasmus, Nikolov, Ivan, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Abdelnour Nocera, José, editor, Kristín Lárusdóttir, Marta, editor, Petrie, Helen, editor, Piccinno, Antonio, editor, and Winckler, Marco, editor

Published
2023
Full Text
View/download PDF

4. Better Real-Life Space Utilization in VR Through a Multimodal Guardian Alternative

Author

Lind, Jonas, Sørensen, Kristian, Lind, Arlonsompoon, Sørensen, Mads, Trærup, Jakob, Nikolov, Ivan, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Abdelnour Nocera, José, editor, Kristín Lárusdóttir, Marta, editor, Petrie, Helen, editor, Piccinno, Antonio, editor, and Winckler, Marco, editor

Published
2023
Full Text
View/download PDF

8. Preliminary Study on the Influence of Visual Cues, Transitional Environments and Tactile Augmentation on the Perception of Scale in VR

Author

Jensen, Tobias Delcour, Kasprzak, Filip, Szekely, Hunor-Gyula, Nikolov, Ivan, Stokholm Høngaard, Jens, Madsen, Claus, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Stephanidis, Constantine, editor, Antona, Margherita, editor, and Ntoa, Stavroula, editor

Published
2020
Full Text
View/download PDF

9. Generating Synthetic Point Clouds of Sewer Networks: An Initial Investigation

Author

Henriksen, Kasper Schøn, Lynge, Mathias S., Jeppesen, Mikkel D. B., Allahham, Moaaz M. J., Nikolov, Ivan A., Haurum, Joakim Bruslund, Moeslund, Thomas B., Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, De Paolis, Lucio Tommaso, editor, and Bourdot, Patrick, editor

Published
2020
Full Text
View/download PDF

10. User-Centered Pipeline for Synthetic Augmentation of Anomaly Detection Datasets †.

Author

Rosbak-Mortensen, Alexander, Jansen, Marco, Muhlig, Morten, Kristensen Tøt, Mikkel Bjørndahl, and Nikolov, Ivan

Subjects
TRAFFIC monitoring, ENGINEERS, USER interfaces, COMPUTER graphics, RESEARCH personnel, USER experience
Abstract

Automatic anomaly detection plays a critical role in surveillance systems but requires datasets comprising large amounts of annotated data to train and evaluate models. Gathering and annotating these data is a labor-intensive task that can become costly. A way to circumvent this is to use synthetic data to augment anomalies directly into existing datasets. This far more diverse scenario can be created and come directly with annotations. This however also poses new issues for the computer-vision engineer and researcher end users, who are not readily familiar with 3D modeling, game development, or computer graphics methodologies and must rely on external specialists to use or tweak such pipelines. In this paper, we extend our previous work of an application that synthesizes dataset variations using 3D models and augments anomalies on real backgrounds using the Unity Engine. We developed a high-usability user interface for our application through a series of RITE experiments and evaluated the final product with the help of deep-learning specialists who provided positive feedback regarding its usability, accessibility, and user experience. Finally, we tested if the proposed solution can be used in the context of traffic surveillance by augmenting the train data from the challenging Street Scene dataset. We found that by using our synthetic data, we could achieve higher detection accuracy. We also propose the next steps to expand the proposed solution for better usability and render accuracy through the use of segmentation pre-processing. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

14. Benchmarking Close-range Structure from Motion 3D Reconstruction Software Under Varying Capturing Conditions

Author

Nikolov, Ivan, Madsen, Claus, Hutchison, David, Editorial Board Member, Kanade, Takeo, Editorial Board Member, Kittler, Josef, Editorial Board Member, Kleinberg, Jon M., Editorial Board Member, Mattern, Friedemann, Editorial Board Member, Mitchell, John C., Editorial Board Member, Naor, Moni, Editorial Board Member, Pandu Rangan, C., Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Terzopoulos, Demetri, Editorial Board Member, Tygar, Doug, Editorial Board Member, Weikum, Gerhard, Series Editor, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Ioannides, Marinos, editor, Fink, Eleanor, editor, Moropoulou, Antonia, editor, Hagedorn-Saupe, Monika, editor, Fresa, Antonella, editor, Liestøl, Gunnar, editor, Rajcic, Vlatka, editor, and Grussenmeyer, Pierre, editor

Published
2016
Full Text
View/download PDF

15. Creating 3D Asset Variations Through 2D Style Transfer and Generated Texture Maps

Author

Nikolov, Ivan Adriyanov

Abstract

Generating 3D object variations through style transfer models applied to their textures is an easy way for creating content for games and XR applications. Most workflows focus on either generating albedo textures only without changing the underlying surface and not touching the underlying surface or transforming the 3D object directly, which is computationally and resource-heavy. In this paper, we present an initial exploration of an in-between solution that aims to combine the style transfer of albedo textures with the generation of additional maps, such as normal, displacement, and roughness. The results show that the pipeline can generate variations based on different styles, which would enable the addition of smaller 3D-style surface features to objects without transforming their meshes. The project code and generated textures will be available at https://github.com/IvanNik17/3D-Assets-From-2D-Style-Transfer

Published
2023

17. ThermalSynth: A Novel Approach for Generating Synthetic Thermal Human Scenarios

Author

Madan, Neelu, primary, Siemon, Mia Sandra Nicole, additional, Gjerde, Magnus Kaufmann, additional, Petersson, Bastian Starup, additional, Grotuzas, Arijus, additional, Esbensen, Malthe Aaholm, additional, Nikolov, Ivan Adriyanov, additional, Philipsen, Mark Philip, additional, Nasrollahi, Kamal, additional, and Moeslund, Thomas B., additional

Published
2023
Full Text
View/download PDF

20. Quantifying the Influence of Surface Texture and Shape on Structure from Motion 3D Reconstructions.

Author

Nielsen, Mikkel Schou, Nikolov, Ivan, Kruse, Emil Krog, Garnæs, Jørgen, and Madsen, Claus Brøndgaard

Subjects
*SURFACE texture, *DIGITAL single-lens reflex cameras, *FOCAL length, *SURFACE topography, *GEOMETRIC surfaces
Abstract

In general, optical methods for geometrical measurements are influenced by the surface properties of the examined object. In Structure from Motion (SfM), local variations in surface color or topography are necessary for detecting feature points for point-cloud triangulation. Thus, the level of contrast or texture is important for an accurate reconstruction. However, quantitative studies of the influence of surface texture on geometrical reconstruction are largely missing. This study tries to remedy that by investigating the influence of object texture levels on reconstruction accuracy using a set of reference artifacts. The artifacts are designed with well-defined surface geometries, and quantitative metrics are introduced to evaluate the lateral resolution, vertical geometric variation, and spatial–frequency information of the reconstructions. The influence of texture level is compared to variations in capturing range. For the SfM measurements, the ContextCapture software solution and a 50 Mpx DSLR camera are used. The findings are compared to results using calibrated optical microscopes. The results show that the proposed pipeline can be used for investigating the influence of texture on SfM reconstructions. The introduced metrics allow for a quantitative comparison of the reconstructions at varying texture levels and ranges. Both range and texture level are seen to affect the reconstructed geometries although in different ways. While an increase in range at a fixed focal length reduces the spatial resolution, an insufficient texture level causes an increased noise level and may introduce errors in the reconstruction. The artifacts are designed to be easily replicable, and by providing a step-by-step procedure of our testing and comparison methodology, we hope that other researchers will make use of the proposed testing pipeline. [ABSTRACT FROM AUTHOR]

Published
2023
Full Text
View/download PDF

27. Convergent Evidence That Oligodendrocyte lineage transcription factor 2 (OLIG2) and Interacting Genes Influence Susceptibility to Schizophrenia

Author

Georgieva, Lyudmila, Moskvina, Valentina, Peirce, Tim, Norton, Nadine, Bray, Nicholas J., Jones, Lesley, Holmans, Peter, MacGregor, Stuart, Zammit, Stanley, Wilkinson, Jennifer, Williams, Hywel, Nikolov, Ivan, Williams, Nigel, Ivanov, Dobril, Davis, Kenneth L., Haroutunian, Vahram, Buxbaum, Joseph D., Craddock, Nick, Kirov, George, Owen, Michael J., and O'Donovan, Michael C.

Published
2006
Full Text
View/download PDF

28. Applied SfM - Capturing and Analysing 3D Surface Data

Author

Nikolov, Ivan Adriyanov

Subjects
metrology, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, virtual reality, 3D reconstruction, surface analysis, Structure from Motion, computer vision
Abstract

This thesis focuses on the problems surrounding Structure from Motion (SfM) data capturing and analysis in the context of 3D surface inspection. The use of 3D point clouds and meshes has become more widely spread, because of the additional level of information that they contain compared to more traditionally used inspection data like 2D images.Through the thesis, each part of the SfM pipeline is examined. From looking at best practices when capturing images both terrestrial and in the air using unmanned aerial vehicles and developing simulation environments for testing capturing setups. Through the development of automatic methods for detecting the absolute scale of the reconstructed surfaces, using additional information from GPS and LiDAR data. Finally, analyzing the resultant reconstructions to determine their accuracy, the presence of noise, and possible use cases, like conveying the surface profile through vibrations and segmenting it into different roughness areas.

Published
2021

34. Auswertung des peri- und postoperativen Verlaufs der verschiedenen Harnableitungen nach radikaler Zystektomie bei hochbetagten Patienten

Author

Nikolov, Ivan, Kuhn, Christoph, and Rohde, Detlef

Subjects
ddc: 610, 610 Medical sciences, Medicine
Abstract

Einleitung: Das Durchschnittsalter der uroonkologischen Patienten in Deutschland steigt wie das demographische Durchschnittsalter kontinuierlich an (Schulzel at al. 2008). Reine Altersgrenzen für ein radikalchirurgisches Vorgehen haben aus unserer Sicht heute keinen Bestand mehr. Wir untersuchten[zum vollständigen Text gelangen Sie über die oben angegebene URL], 66. Kongress der Nordrhein-Westfälischen Gesellschaft für Urologie

Published
2020
Full Text
View/download PDF

35. Generating Synthetic Point Clouds of Sewer Networks:An Initial Investigation

Author

Henriksen, Kasper Schøn, Lynge, Mathias Stougaard, Düring Bech Jeppesen, Mikkel, Allahham, Moaaz Mohamed Jamal, Nikolov, Ivan Adriyanov, Haurum, Joakim Bruslund, Moeslund, Thomas B., De Paolis, Lucio Tommaso, and Bourdot, Patrick

Subjects
Sewer inspection, Point Cloud, structured domain randomization, synthetic data, time-of-flight camera, simulation
Abstract

Automatic robot inspections of sewer systems are progressively becoming more used for extending the lifetime of sewers and lowering the costs of maintenance. These automatic systems rely on machine learning and the acquisition of varied training data is therefore necessary. Capturing such data can be a costly and time consuming process. This paper proposes a system for generation and acquisition of synthetic training data from sewer systems. The system utilizes Structured Domain Randomization (SDR) for the generation of the sewer systems and an approximated model of a Pico Flexx Time-of-Flight camera for capturing depth and point cloud data from the generated sewer network. We evaluate the proposed system by comparing its output to ground truth data acquired from a Pico Flexx sensor in sewer pipes. We demonstrate that on average our system provides an absolute error of 5.78 ± 8.92 and 7.58 ± 8.68 mm, between data captured from real life and our proposed system, for two different scenarios. These results prove satisfactory for capturing training data. The code is publicly available at https://​bitbucket.​org/​aauvap/​syntheticsewerpi​pes/​src/​master/​.

Published
2020

36. Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls

Author

Burton, Paul R., Clayton, David G., Cardon, Lon R., Craddock, Nick, Deloukas, Panos, Duncanson, Audrey, Kwiatkowski, Dominic P., McCarthy, Mark I., Ouwehand, Willem H., Samani, Nilesh J., Todd, John A., Donnelly, Peter, Barrett, Jeffrey C., Davison, Dan, Easton, Doug, Evans, David, Leung, Hin-Tak, Marchini, Jonathan L., Morris, Andrew P., Spencer, Chris C. A., Tobin, Martin D., Attwood, Antony P., Boorman, James P., Cant, Barbara, Everson, Ursula, Hussey, Judith M., Jolley, Jennifer D., Knight, Alexandra S., Koch, Kerstin, Meech, Elizabeth, Nutland, Sarah, Prowse, Christopher V., Stevens, Helen E., Taylor, Niall C., Walters, Graham R., Walker, Neil M., Watkins, Nicholas A., Winzer, Thilo, Jones, Richard W., McArdle, Wendy L., Ring, Susan M., Strachan, David P., Pembrey, Marcus, Breen, Gerome, St Clair, David, Caesar, Sian, Gordon-Smith, Katherine, Jones, Lisa, Fraser, Christine, Green, Elaine K., Grozeva, Detelina, Hamshere, Marian L., Holmans, Peter A., Jones, Ian R., Kirov, George, Moskvina, Valentina, Nikolov, Ivan, O'Donovan, Michael C., Owen, Michael J., Collier, David A., Elkin, Amanda, Farmer, Anne, Williamson, Richard, McGuffin, Peter, Young, Allan H., Ferrier, I. Nicol, Ball, Stephen G., Balmforth, Anthony J., Barrett, Jennifer H., Bishop, D. Timothy, Iles, Mark M., Maqbool, Azhar, Yuldasheva, Nadira, Hall, Alistair S., Braund, Peter S., Dixon, Richard J., Mangino, Massimo, Stevens, Suzanne, Thompson, John R., Bredin, Francesca, Tremelling, Mark, Parkes, Miles, Drummond, Hazel, Lees, Charles W., Nimmo, Elaine R., Satsangi, Jack, Fisher, Sheila A., Forbes, Alastair, Lewis, Cathryn M., Onnie, Clive M., Prescott, Natalie J., Sanderson, Jeremy, Mathew, Christopher G., Barbour, Jamie, Mohiuddin, M. Khalid, Todhunter, Catherine E., Mansfield, John C., Ahmad, Tariq, Cummings, Fraser R., Jewell, Derek P., Webster, John, Brown, Morris J., Lathrop, G. Mark, Connell, John, Dominiczak, Anna, Marcano, Carolina A. Braga, Burke, Beverley, Dobson, Richard, Gungadoo, Johannie, Lee, Kate L., Munroe, Patricia B., Newhouse, Stephen J., Onipinla, Abiodun, Wallace, Chris, Xue, Mingzhan, Caulfield, Mark, Farrall, Martin, Barton, Anne, Bruce, Ian N., Donovan, Hannah, Eyre, Steve, Gilbert, Paul D., Hider, Samantha L., Hinks, Anne M., John, Sally L., Potter, Catherine, Silman, Alan J., Symmons, Deborah P. M., Thomson, Wendy, Worthington, Jane, Dunger, David B., Widmer, Barry, Frayling, Timothy M., Freathy, Rachel M., Lango, Hana, Perry, John R. B., Shields, Beverley M., Weedon, Michael N., Hattersley, Andrew T., Hitman, Graham A., Walker, Mark, Elliott, Kate S., Groves, Christopher J., Lindgren, Cecilia M., Rayner, Nigel W., Timpson, Nicholas J., Zeggini, Eleftheria, Newport, Melanie, Sirugo, Giorgio, Lyons, Emily, Vannberg, Fredrik, Hill, Adrian V. S., Bradbury, Linda A., Farrar, Claire, Pointon, Jennifer J., Wordsworth, Paul, Brown, Matthew A., Franklyn, Jayne A., Heward, Joanne M., Simmonds, Matthew J., Gough, Stephen C. L., Seal, Sheila, Stratton, Michael R., Rahman, Nazneen, Ban, Maria, Goris, An, Sawcer, Stephen J., Compston, Alastair, Conway, David, Jallow, Muminatou, Rockett, Kirk A., Bumpstead, Suzannah J., Chaney, Amy, Downes, Kate, Ghori, Mohammed J. R., Gwilliam, Rhian, Hunt, Sarah E., Inouye, Michael, Keniry, Andrew, King, Emma, McGinnis, Ralph, Potter, Simon, Ravindrarajah, Rathi, Whittaker, Pamela, Widden, Claire, Withers, David, Cardin, Niall J., Ferreira, Teresa, Pereira-Gale, Joanne, Hallgrimsdottir, Ingileif B., Howie, Bryan N., Su, Zhan, Teo, Yik Ying, Vukcevic, Damjan, Bentley, David, and Compston, Alistair

Subjects
Environmental issues, Science and technology, Zoology and wildlife conservation
Abstract

Author(s): The Wellcome Trust Case Control Consortium; Management Committee; Paul R. Burton [1]; David G. Clayton [2]; Lon R. Cardon [3]; Nick Craddock [4]; Panos Deloukas [5]; Audrey Duncanson [6]; [...]

Published
2007
Full Text
View/download PDF

47. Common polygenic variation contributes to risk of schizophrenia and bipolar disorder

Author

Purcell, Shaun M., Wray, Naomi R., Stone, Jennifer L., Visscher, Peter M., OʼDonovan, Michael C., Sullivan, Patrick F., Sklar, Pamela, Ruderfer, Douglas M., McQuillin, Andrew, Morris, Derek W., OʼDushlaine, Colm T., Corvin, Aiden, Holmans, Peter A., Macgregor, Stuart, Gurling, Hugh, Blackwood, Douglas H. R., Craddock, Nick J., Gill, Michael, Hultman, Christina M., Kirov, George K., Lichtenstein, Paul, Muir, Walter J., Owen, Michael J., Pato, Carlos N., Scolnick, Edward M., St Clair, David, Williams, Nigel M., Georgieva, Lyudmila, Nikolov, Ivan, Norton, N., Williams, H., Toncheva, Draga, Milanova, Vihra, Thelander, Emma F., Sullivan, Patrick, Kenny, Elaine, Quinn, Emma M., Choudhury, Khalid, Datta, Susmita, Pimm, Jonathan, Thirumalai, Srinivasa, Puri, Vinay, Krasucki, Robert, Lawrence, Jacob, Quested, Digby, Bass, Nicholas, Crombie, Caroline, Fraser, Gillian, Leh Kuan, Soh, Walker, Nicholas, McGhee, Kevin A., Pickard, Ben, Malloy, Pat, Maclean, Alan W., Van Beck, Margaret, Pato, Michele T., Medeiros, Helena, Middleton, Frank, Carvalho, Celia, Morley, Christopher, Fanous, Ayman, Conti, David, Knowles, James A., Paz Ferreira, Carlos, Macedo, Antonio, Azevedo, Helena M., Kirby, Andrew N., Ferreira, Manuel A. R., Daly, Mark J., Chambert, Kimberly, Kuruvilla, Finny, Gabriel, Stacey B., Ardlie, Kristin, and Moran, Jennifer L.

Published
2009
Full Text
View/download PDF

48. Rare chromosomal deletions and duplications increase risk of schizophrenia

Author

Stone, Jennifer L., O'Donovan, Michael C., Gurling, Hugh, Kirov, George K., Blackwood, Douglas H.R., Corvin, Aiden, Craddock, Nick J., Gill, Michael, Hultman, Christina M., Lichtenstein, Paul, McQuillin, Andrew, Pato, Carlos N., Ruderfer, Douglas M., Owen, Michael J., St Clair, David, Sullivan, Patrick F., Macgregor, Stuart, Morris, Derek W., O'Dushlaine, Colm T., Daly, Mark J., Visscher, Peter M., Holmans, Peter A., Scolnick, Edward M., Williams, Nigel M., Georgieva, Lucy, Nikolov, Ivan, Norton, N., Williams, H., Toncheva, Draga, Milanova, Vihra, Thelander, Emma F., Sullivan, Patrick, Kenny, Elaine, Waddington, John L., Choudhury, Khalid, Datta, Susmita, Pimm, Jonathan, Thirumalai, Srinivasa, Puri, Vinay, Krasucki, Robert, Lawrence, Jacob, Quested, Digby, Bass, Nicholas, Curtis, David, Crombie, Caroline, Fraser, Gillian, Kwan, Soh Leh, Walker, Nicholas, Muir, Walter J., McGhee, Kevin A., Pickard, Ben, Malloy, Pat, Maclean, Alan W., Van Beck, Margaret, Pato, Michele T., Medeiros, Helena, Middleton, Frank, Carvalho, Celia, Morley, Christopher, Fanous, Ayman, Conti, David, Knowles, James A., Ferreira, Carlos Paz, Macedo, Antonio, Azevedo, M. Helena, McCarroll, Steve A., Daly, Mark, Purcell, Shaun M., Sklar, Pamela, Chambert, Kimberly, Korn, Joshua, Gates, Casey, Gabriel, Stacey B., Mahon, Scott, and Ardlie, Kristen

Published
2008
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results