Maia Rohm
Mag. Dr. — Position: Weitere Mitarbeiterin
Contact
| maia.rohm@tuwien.ac.at | |
| Office | 1040 Wien, Favoritenstrasse 11 • Room HG0409 • Map |
| Office Hours | By Appointment |
| Phone | +43-1-58801-18857 |
2018
| Guided projections for analyzing the structure of high-dimensional data A powerful data transformation method named guided projections is proposed creating new possibilities to reveal the group structure of… | T. Ortner, P. Filzmoser, M. Rohm, C. Breiteneder, S. Brodinova | Details |
2017
| Finding groups in large and high-dimensional data using a k-means-based algorithm S. Brodinova, P. Filzmoser, T. Ortner, C. Breiteneder, M. Zaharieva: "Finding groups in large and high-dimensional data using a k-means-based… | S. Brodinova, P. Filzmoser, T. Ortner, C. Breiteneder, M. Zaharieva | Details |
| Retrieving Diverse Social Images at MediaEval 2017: Challenges, Dataset and Evaluation This paper provides an overview of the Retrieving Diverse Social Images task that is organized as part of the MediaEval 2017 Benchmarking Initiative… | M. Zaharieva, B. Ionescu, A. Ginsca, R. Santos, H. Müller | Details |
| Robust and sparse clustering for high-dimensional data We introduce a robust and sparse clustering procedure for high-dimensional data. The robustness aspect is addressed by a weighting function… | S. Brodinova, P. Filzmoser, T. Ortner, M. Zaharieva, C. Breiteneder | Details |
| Grouping and outlier detection using robust sparse clustering S. Brodinova, P. Filzmoser, T. Ortner, M. Zaharieva, C. Breiteneder: "Grouping and outlier detection using robust sparse clustering"; Talk: Olomouc… | S. Brodinova, P. Filzmoser, T. Ortner, M. Zaharieva, C. Breiteneder | Details |
| Local projection for outlier detection T. Ortner, P. Filzmoser, S. Brodinova, M. Zaharieva, C. Breiteneder: "Local projection for outlier detection"; Talk: Olomouc Days of Applied… | T. Ortner, P. Filzmoser, S. Brodinova, M. Zaharieva, C. Breiteneder | Details |
| Diversity and credibility for social Images and image retrieval Social media has established itself as an inextricable component of today´s society. Images make up a large proportion of items shared on social… | I. Bogdan, M. Lupu, M. Rohm, A. Ginsca, H. Müller | Details |
| Clustering of imbalanced high-dimensional media data S. Brodinova, M. Zaharieva, P. Filzmoser, T. Ortner, C. Breiteneder: "Clustering of imbalanced high-dimensional media data"; Advances in Data… | S. Brodinova, M. Zaharieva, P. Filzmoser, T. Ortner, C. Breiteneder | Details |
| Unsupervised group feature selection for media classification The selection of an appropriate feature set is crucial for the efficient analysis of any media collection. In general, feature selection strongly… | M. Zaharieva, C. Breiteneder, M. Hudec | Details |
2016
| Guided projections for analysising the structure of high dimensional data T. Ortner, P. Filzmoser, M. Zaharieva, C. Breiteneder, S. Brodinova: "Guided projections for analysising the structure of high dimensional data";… | T. Ortner, P. Filzmoser, M. Zaharieva, C. Breiteneder, S. Brodinova | Details |
| An Adaptive Clustering Approach for the Diversification of Image Retrieval Results In this paper, we explore the application of an adaptive clustering approach for the diversification of image retrieval results in the context of the… | M. Zaharieva | Details |
| Retrieving Diverse Social Images at MediaEval 2016: Challenge, Dataset and Evaluation This paper provides an overview of the Retrieving Diverse Social Images task that is organized as part of the MediaEval 2016 Benchmarking Initiative… | B. Ionescu, A. Gînscǎ, M. Zaharieva, B. Boteanu, M. Lupu, H. Müller | Details |
| Forward Projection for High-Dimensional Data We provide a novel view on group structure in data. Projecting observations onto a subspace spanned by a small selection of observations, we… | T. Ortner, P. Filzmoser, S. Brodinova, M. Zaharieva, C. Breiteneder | Details |
| Group Detection in the Context of Imbalanced Data The problem of group detection with no prior knowledge, i.e clustering, is one of the most important tasks in data analysis. It has been addressed in… | S. Brodinova, M. Zaharieva, P. Filzmoser, T. Ortner, C. Breiteneder | Details |
| Evaluation of robust PCA for supervised audio outlier detection Outliers often reveal crucial information about the underlying data such as the presence of unusual observations that require for in-depth analysis.… | S. Brodinova, T. Ortner, P. Filzmoser, M. Zaharieva, C. Breiteneder | Details |
| Model-based Video Content Representation Recurring visual elements in videos commonly represent central content entities, such as main characters and dominant objects. The automated… | L. Diem, M. Zaharieva | Details |
| Video Content Representation Using Recurring Regions Detection In this work we present an approach for video content representation based on the detection of recurring visual elements or regions. We hypothesize… | L. Diem, M. Zaharieva | Details |
| Group Feature Selection for Audio-Based Video Genre Classification The performance of video genre classification approaches strongly depends on the selected feature set. Feature selection requires for expert… | G. Sageder, M. Zaharieva, C. Breiteneder | Details |
2015
| Media Synchronization and Sub-Event Detection in Multi-User Image Collections Personal media capturing devices, such as smartphones or personal image and video cameras, are rarely synchronized. As a result, common tasks, like… | M. Zaharieva, M. Riegler | Details |
| Simulation of Robust PCA for Supervised Audio Outlier Detection S. Brodinova, T. Ortner, P. Filzmoser, M. Zaharieva, C. Breiteneder: "Simulation of Robust PCA for Supervised Audio Outlier Detection"; Talk:… | S. Brodinova, T. Ortner, P. Filzmoser, M. Zaharieva, C. Breiteneder | Details |
| MIS @ Retrieving Diverse Social Images Task 2015 In this paper, we describe our approach for the MediaEval 2015 Retrieving Diverse Social Images Task. The proposed approach exploits available… | M. Zaharieva, L. Diem | Details |
| Social Event Mining in Large Photo Collections A significant part of publicly available photos on the Internet depicts a variety of different social events. In order to organize this steadily… | M. Zaharieva, M. Zeppelzauer, M. Fabro, D. Schopfhauser | Details |
| Interpretable Video Representation The immense amount of available video data poses novel requirements for video representation approaches by means of focusing on central and relevant… | L. Diem, M. Zaharieva | Details |
| Cross-Platform Social Event Detection A large part of media shared on online platforms such as Flickr and YouTube is captured at various social events (such as music festivals,… | M. Zaharieva, M. Fabro, M. Zeppelzauer | Details |
| Evaluation of Robust PCA for Supervised Audio Outlier Detection Outliers often reveal crucial information about the underlying data such as the presence of unusual observations that require for in-depth analysis.… | S. Brodinova, T. Ortner, P. Filzmoser, M. Zaharieva, C. Breiteneder | Details |
2014
| Multimodal Synchronization of Image Galleries This paper describes our contribution to the MediaEval 2014 task on the Synchronization of multi-user Event Media (SEM). We propose two multimodal… | M. Zaharieva, M. Riegler, M. Fabro | Details |
| Clustering and Retrieval of Social Events in Flickr This paper describes our contributions to the Social Event Detection (SED) task as part of the MediaEval Benchmark 2014. We first present an… | M. Zaharieva, P. Schopfhauser, M. Fabro, M. Zeppelzauer | Details |
| A Unified Framework for Retrieving Diverse Social Images In this paper we explore the performance of a generic, unified framework for the retrieval of relevant and diverse images from social photo… | M. Zaharieva, P. Schwab | Details |
| Unsupervised selection of robust audio feature subsets Feature selection is applied to identify relevant and complementary features from a given high-dimensional feature set. In general, existing… | G. Sageder, M. Zaharieva, M. Zeppelzauer | Details |
2013
| Unsupervised Clustering of Social Events This paper describes our contribution to the social event de- tection (SED) task of the MediaEval Benchmark 2013. We present a robust unsupervised… | M. Zeppelzauer, M. Zaharieva, M. Fabro | Details |
| Automated Social Event Detection in Large Photo Collections M. Zaharieva, M. Zeppelzauer, C. Breiteneder: "Automated Social Event Detection in Large Photo Collections"; in: "ICMR '13 Proceedings of the 3rd ACM… | M. Zaharieva, M. Zeppelzauer, C. Breiteneder | Details |
2012
| Recurring Element Detection in Movies Recurring elements in movies contribute significantly to the development of narration, themes, or even mood. The detection of such elements is… | M. Zaharieva, C. Breiteneder | Details |
| A Generic Approach for Social Event Detection in Large Photo Collections In this paper we explore the performance of a generic methodology for the detection of social events in large photo collections. The proposed… | M. Zeppelzauer, M. Zaharieva, C. Breiteneder | Details |
2011
| Retrieval of Visual Composition in Film The spatial arrangement of visual elements of an image, i.e. the visual composition, is a research subject in the domain of visual arts which include… | D. Mitrovic, M. Zeppelzauer, M. Zaharieva, C. Breiteneder | Details |
| Features in visual media analysis Today, film analysis is still a tedious process performed mostly manually by film experts. Existing computer vision approaches aim at improved… | M. Zaharieva | Details |
| Retrieval of motion composition in film M. Zeppelzauer, M. Zaharieva, D. Mitrovic, C. Breiteneder: "Retrieval of motion composition in film"; Digital Creativity, 22 (2011), 4; 219 - 234. | M. Zeppelzauer, M. Zaharieva, D. Mitrovic, C. Breiteneder | Details |
| Identification of ancient coins based on fusion of shape and local features R. Huber-Mörk, S. Zambanini, M. Zaharieva, M. Kampel: "Identification of ancient coins based on fusion of shape and local features"; Machine Vision… | R. Huber-Mörk, S. Zambanini, M. Zaharieva, M. Kampel | Details |
| Film Analysis of Archive Documentaries Film experts, archives and museums state highly demanding requirements for automated film analysis. The experimental style of archive documentaries… | M. Zaharieva, D. Mitrovic, M. Zeppelzauer, C. Breiteneder | Details |
2010
| Camera Take Reconstruction In this paper we focus on a novel issue in the field of video retrieval stemming from film analysis, namely the investigation of film montage… | M. Zaharieva, M. Zeppelzauer, C. Breiteneder, D. Mitrovic | Details |
| A Novel Trajectory Clustering Approach for Motion Segmentation We propose a novel clustering scheme for spatio-temporal segmentation of sparse motion fields obtained from feature tracking. The approach allows for… | M. Zeppelzauer, M. Zaharieva, D. Mitrovic, C. Breiteneder | Details |
| Archive Film Comparison In this paper, the authors present an approach for video comparison, in which an instantiated framework allows for the easy comparison of different… | M. Zaharieva, M. Zeppelzauer, D. Mitrovic, C. Breiteneder | Details |
2009
| Finding the Missing Piece: Content-Based Video Comparison The contribution of this paper consists of a framework for video comparison that allows for the analysis of different movie versions. Furthermore, a… | M. Zaharieva, M. Zeppelzauer, D. Mitrovic, C. Breiteneder | Details |
2008
| Evaluation of content-based Features for User-Centred Image Retrieval in Small Media Collections H. Eidenberger, M. Zaharieva: "Evaluation of content-based Features for User-Centred Image Retrieval in Small Media Collections"; Talk: SPIE IS&T… | H. Eidenberger, M. Zaharieva | Details |
2007
| Semantics in Content-based Multimedia Retrieval H. Eidenberger, M. Zaharieva: "Semantics in Content-based Multimedia Retrieval"; in: "Multimedia Semantics - The Role of Metadata", Springer, 2007,… | H. Eidenberger, M. Zaharieva | Details |