Konstantinos Apostolidis

Bio: Konstantinos Apostolidis is an academic researcher from Information Technology Institute. The author has contributed to research in topics: Web application & Computer science. The author has an hindex of 5, co-authored 17 publications receiving 76 citations.

The InVID Plug-in: Web Video Verification on the Browser

Abstract: This paper presents a novel open-source browser plug-in that aims at supporting journalists and news professionals in their efforts to verify user-generated video. The plug-in, which is the result of an iterative design thinking methodology, brings together a number of sophisticated multimedia analysis components and third party services, with the goal of speeding up established verification workflows and making it easy for journalists to access the results of different services that were previously used as standalone tools. The tool has been downloaded several hundreds of times and is currently used by journalists worldwide, after being tested by Agence France-Presse (AFP) and Deutsche Welle (DW) journalists and media researchers for a few months. The tool has already helped debunk a number of fake videos.

Image Aesthetics Assessment Using Fully Convolutional Neural Networks

Abstract: This paper presents a new method for assessing the aesthetic quality of images. Based on the findings of previous works on this topic, we propose a method that addresses the shortcomings of existing ones, by: (a) Making possible to feed higher-resolution images in the network, by introducing a fully convolutional neural network as the classifier. (b) Maintaining the original aspect ratio of images in the input of the network, to avoid distortions caused by re-scaling. And (c) combining local and global features from the image for making the assessment of its aesthetic quality. The proposed method is shown to achieve state of the art results on a standard large-scale benchmark dataset.

A Web Service for Video Summarization

Abstract: This paper presents a Web service that supports the automatic generation of video summaries for user-submitted videos. The developed Web application decomposes the video into segments, evaluates the fitness of each segment to be included in the video summary and selects appropriate segments until a pre-defined time budget is filled. The integrated deep-learning-based video analysis and summarization technologies exhibit state-of-the-art performance and, by exploiting the processing capabilities of modern GPUs, offer faster than real-time processing. Configurations for generating video summaries that fulfill the specifications for posting on the most common video sharing platforms and social networks are available in the user interface of this application, enabling the one-click generation of distribution-channel-specific summaries.

VERGE in VBS 2019

Abstract: This paper presents VERGE, an interactive video retrieval engine that enables browsing and searching into video content. The system implements various retrieval modalities, such as visual or textual search, concept detection and clustering, as well as a multimodal fusion and a reranking capability. All results are displayed in a graphical user interface in an efficient and friendly manner.

Pattern Recognition and Machine Learning

Abstract: Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Detection and visualization of misleading content on Twitter

Abstract: The problems of online misinformation and fake news have gained increasing prominence in an age where user-generated content and social media platforms are key forces in the shaping and diffusion of news stories. Unreliable information and misleading content are often posted and widely disseminated through popular social media platforms such as Twitter and Facebook. As a result, journalists and editors are in need of new tools that can help them speed up the verification process for content that is sourced from social media. Motivated by this need, in this paper, we present a system that supports the automatic classification of multimedia Twitter posts into credible or misleading. The system leverages credibility-oriented features extracted from the tweet and the user who published it, and trains a two-step classification model based on a novel semisupervised learning scheme. The latter uses the agreement between two independent pretrained models on new posts as guiding signals for retraining the classification model. We analyze a large labeled dataset of tweets that shared debunked fake and confirmed real images and videos, and show that integrating the newly proposed features, and making use of bagging in the initial classifiers and of the semisupervised learning scheme, significantly improves classification accuracy. Moreover, we present a Web-based application for visualizing and communicating the classification results to end users.

On Influential Trends in Interactive Video Retrieval: Video Browser Showdown 2015–2017

Abstract: 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 video retrieval scenarios emerged as well, which challenge the state-of-the-art video retrieval approaches. Despite recent advances in content analysis, video retrieval can still benefit from involving the human user in the loop. We present our experience with a class of interactive video retrieval scenarios and our methodology to stimulate the evolution of new interactive video retrieval approaches. More specifically, the video browser showdown evaluation campaign is thoroughly analyzed, focusing on the years 2015–2017. Evaluation scenarios, objectives, and metrics are presented, complemented by the results of the annual evaluations. The results reveal promising interactive video retrieval techniques adopted by the most successful tools and confirm assumptions about the different complexity of various types of interactive retrieval scenarios. A comparison of the interactive retrieval tools with automatic approaches (including fully automatic and manual query formulation) participating in the TRECVID 2016 ad hoc video search task is discussed. Finally, based on the results of data analysis, a substantial revision of the evaluation methodology for the following years of the video browser showdown is provided.

Video Interaction Tools: A Survey of Recent Work

Abstract: Digital video enables manifold ways of multimedia content interaction. Over the last decade, many proposals for improving and enhancing video content interaction were published. More recent work particularly leverages on highly capable devices such as smartphones and tablets that embrace novel interaction paradigms, for example, touch, gesture-based or physical content interaction. In this article, we survey literature at the intersection of Human-Computer Interaction and Multimedia. We integrate literature from video browsing and navigation, direct video manipulation, video content visualization, as well as interactive video summarization and interactive video retrieval. We classify the reviewed works by the underlying interaction method and discuss the achieved improvements so far. We also depict a set of open problems that the video interaction community should address in future.

Disinformation and Propaganda – Impact on the Functioning of the Rule of Law in the EU and its Member States

Abstract: This study, commissioned by the European Parliament’s Policy Department for Citizens’ Rights and Constitutional Affairs and requested by the European Parliament’s Committee on Civil Liberties, Justice and Home Affairs, assesses the impact of disinformation and strategic political propaganda disseminated through online social media sites. It examines effects on the functioning of the rule of law, democracy and fundamental rights in the EU and its Member States. The study formulates recommendations on how to tackle this threat to human rights, democracy and the rule of law. It specifically addresses the role of social media platform providers in this regard.