A5010725699- Advanced Image and Video Retrieval Techniques
- Video Analysis and Summarization
- Multimodal Machine Learning Applications
- Image Retrieval and Classification Techniques
- Data Management and Algorithms
- Domain Adaptation and Few-Shot Learning
- Algorithms and Data Compression
- Topic Modeling
- Multimedia Communication and Technology
- Network Security and Intrusion Detection
- Internet Traffic Analysis and Secure E-voting
- Advanced Proteomics Techniques and Applications
- Metabolomics and Mass Spectrometry Studies
- Data Mining Algorithms and Applications
- Advanced Database Systems and Queries
- Data Visualization and Analytics
- Natural Language Processing Techniques
- Music and Audio Processing
- Digital Media Forensic Detection
- Anomaly Detection Techniques and Applications
- Spam and Phishing Detection
- Geographic Information Systems Studies
- Web Data Mining and Analysis
- Recommender Systems and Techniques
- Mass Spectrometry Techniques and Applications
Charles University
2016-2025
Joanneum Research
2023
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo"
2023
HTW Berlin - University of Applied Sciences
2023
University of Klagenfurt
2023
The last decade has seen innovations that make video recording, manipulation, storage, and sharing easier than ever before, thus impacting many areas of life. New retrieval scenarios emerged as well, which challenge the state-of-the-art approaches. Despite recent advances in content analysis, can still benefit from involving human user loop. We present our experience with a class interactive methodology to stimulate evolution new More specifically, browser showdown evaluation campaign is...
Despite the fact that automatic content analysis has made remarkable progress over last decade - mainly due to significant advances in machine learning interactive video retrieval is still a very challenging problem, with an increasing relevance practical applications. The Video Browser Showdown (VBS) annual evaluation competition pushes limits of state-of-the-art tools, tasks, data, and metrics. In this paper, we analyse results outcome 8th iteration VBS detail. We first give overview novel...
The Lifelog Search Challenge (LSC) is an international content retrieval competition that evaluates search for personal lifelog data. At the LSC, content-based performed over a multi-modal dataset, continuously recorded by lifelogger 27 days, consisting of multimedia content, biometric data, human activity and information activities In this work, we report on first LSC took place in Yokohama, Japan 2018 as special workshop at ACM International Conference Multimedia Retrieval (ICMR 2018). We...
For the sixth time since 2018, Lifelog Search Challenge (LSC) was organized as a comparative benchmarking exercise for various interactive lifelog search systems. The goal of this international competition is to test system capabilities access large multimodal lifelogs. LSC'23 attracted twelve participanting teams, each whom had developed competitive retrieval system. benchmark in front live audience at LSC workshop ACM ICMR'23. As previous editions, introductory paper presents and...
For the seventh time since 2018, Lifelog Search Challenge (LSC) benchmarked interactive lifelog search systems in a live challenge. The LSC goal is to comparatively evaluate system capabilities access large multimodal lifelogs comprising hundreds of thousands records. LSC'24 attracted an unprecedented record number twenty-one participating teams, where each team proposes innovative ideas implemented new or already established retrieval systems. benchmark was organised front audience at...
This paper conducts a thorough examination of the 12th Video Browser Showdown (VBS) competition, which is well-established international benchmarking campaign for interactive video search systems. The annual VBS competition has witnessed steep rise in popularity multimodal embedding-based approaches retrieval. majority thirteen systems participating 2023 utilized CLIP-based cross-modal model, allowing specification free-form text queries to visual content. shared emphasis on joint embedding...
Interactive video retrieval tools developed over the past few years are emerging as powerful alternatives to automatic approaches by giving user more control well responsibilities. Current research tries identify best combinations of image, audio and text features that combined with innovative UI design maximize performance. We present last installment Video Browser Showdown 2015 which was held in conjunction International Conference on MultiMedia Modeling (MMM 2015) has stated aim pushing...
This work summarizes the findings of 7th iteration Video Browser Showdown (VBS) competition organized as a workshop at 24th International Conference on Multimedia Modeling in Bangkok. The focuses video retrieval scenarios which searched scenes were either previously observed or described by another person (i.e., an example shot is not available). During event, nine teams competed with their tools providing access to shared collection 600 hours content. Evaluation objectives, rules, scoring,...
The Lifelog Search Challenge (LSC) is an annual comparative benchmarking activity for comparing approaches to interactive retrieval from multi-modal lifelogs. LSC'20, the third such challenge, attracts fourteen participants with their lifelog systems. These systems are comparatively evaluated in front of a live-audience at LSC workshop ACM ICMR'20 Dublin, Ireland. This overview motivates presents dataset and system configuration used briefly participating teams.
The Lifelog Search Challenge (LSC) is an annual benchmarking challenge for comparing approaches to interactive retrieval from multi-modal lifelogs. LSC'21, the fourth challenge, attracted sixteen participants, each of which had developed systems large multimodal These participated in a comparative evaluation front online live-audience at LSC workshop ACM ICMR'21. This overview presents motivation lifelog dataset used competition, and participating systems.
Comprehensive and fair performance evaluation of information retrieval systems represents an essential task for the current age. Whereas Cranfield-based evaluations with benchmark datasets support development models, significant efforts are required also user-oriented that try to boost interactive search approach. This article presents findings from 9th Video Browser Showdown, a competition focuses on legitimate comparison designed challenging known-item tasks over large video collection....
For the fifth time since 2018, Lifelog Search Challenge (LSC) facilitated a benchmarking exercise to compare interactive search systems designed for multimodal lifelogs. LSC'22 attracted nine participating research groups who developed lifelog retrieval enabling fast and effective access The competed in front of hybrid audience at LSC workshop ACM ICMR'22. This paper presents an introduction workshop, new (larger) dataset used competition, introduces systems.
The Lifelog Search Challenge (LSC) is an interactive benchmarking evaluation workshop for lifelog retrieval systems. challenge was first organised in 2018 aiming to find the system that can quickly retrieve relevant images a given semantic query. This paper provides analysis of performance all 17 systems participating 4th LSC held at 2021 Annual ACM International Conference on Multimedia Retrieval (ICMR). LSC'21 largest effort comparing different approaches seen thus far. Findings from...
Although automatic shot transition detection approaches are already investigated for more than two decades, an effective universal human-level model was not proposed yet. Even common transitions like hard cuts or simple gradual changes, the potential diversity of analyzed video contents may still lead to both false hits and dismissals. Recently, deep learning-based significantly improved accuracy using 3D convolutional architectures artificially created training data. Nevertheless, one...
Searching for one particular scene in a large video collection (known-item search) represents challenging task retrieval systems. According to the recent results reached at evaluation campaigns, even respected approaches based on machine learning do not help solve easily many cases. Hence, addition effective automatic multimedia annotation and embedding, interactive search is recommended as well. This paper presents comprehensive description of an framework VIRET that successfully...