scholarly journals Scaling up Cast Face Detection in Videos at Globo

2021 ◽  
Author(s):  
Felipe A. Ferreira ◽  
Bruno P. Oliveira ◽  
Rodrigo V. Kassick ◽  
Vinícius Furlan ◽  
Hélio Lopes
Keyword(s):  
Recommender Systems ◽  
Face Detection ◽  
Search Engines ◽  
Scaling Up ◽  
Video Stream ◽  
Video Content ◽  
Industry Sector ◽  
Production And Consumption ◽  
Metadata Generation

It has been recognized that a significant increase in the production and consumption of video content occurred in the last decade. Many entertainment companies, like Globo, face challenges regarding video metadata generation. The objective of this paper is to present a suitable architecture for the Globo Group to automatically identify actors that appear in each scene of a video stream, generating new metadata annotations that can be used by recommender systems and search engines among different other applications in this industry sector.

Enhancing Citizens' Participation via Recommender Systems

2020 ◽  
pp. 624-650
Author(s):  
Luis Terán
Keyword(s):  
Decision Making ◽  
Semantic Web ◽  
Private Sector ◽  
Web 2.0 ◽  
Recommender Systems ◽  
Search Engines ◽  
Information Overload ◽  
Relevant Information ◽  
Research Topic ◽  
Government Services

With the introduction of Web 2.0, which includes users as content generators, finding relevant information is even more complex. To tackle this problem of information overload, a number of different techniques have been introduced, including search engines, Semantic Web, and recommender systems, among others. The use of recommender systems for e-Government is a research topic that is intended to improve the interaction among public administrations, citizens, and the private sector through reducing information overload on e-Government services. In this chapter, the use of recommender systems on eParticipation is presented. A brief description of the eGovernment Framework used and the participation levels that are proposed to enhance participation. The highest level of participation is known as eEmpowerment, where the decision-making is placed on the side of citizens. Finally, a set of examples for the different eParticipation types is presented to illustrate the use of recommender systems.

Copy Detection Using Graphical Model

2012 ◽  
pp. 261-279
Author(s):  
Shikui Wei ◽  
Yao Zhao ◽  
Zhenfeng Zhu
Keyword(s):  
Graphical Model ◽  
Graph Model ◽  
Video Stream ◽  
Temporal Consistency ◽  
Video Content ◽  
Video Copy Detection ◽  
Copy Detection ◽  
Video Sharing ◽  
Frame Fusion ◽  
Temporal Localization

With the growing popularity of video sharing websites and editing tools, it is easy for people to involve the video content from different sources into their own work, which raises the copyright problem. Content-based video copy detection attempts to track the usage of the copyright-protected video content by using video analysis techniques, which deals with not only whether a copy occurs in a query video stream but also where the copy is located and where the copy is originated from. While a lot of work has addressed the problem with good performance, less effort has been made to consider the copy detection problem in the case of a continuous query stream, for which precise temporal localization and some complex video transformations like frame insertion and video editing need to be handled. In this chapter, the authors attack the problem by employing the graphical model to facilitate the frame fusion based video copy detection approach. The key idea is to convert frame fusion problem into graph model decoding problem with the temporal consistency constraint and three relaxed constraints. This work employs the HMM model to perform frame fusion and propose a Viterbi-like algorithm to speedup frame fusion process.

scholarly journals Recommendation as Collaboration in Web Search

AI Magazine ◽  
2011 ◽  
Vol 32 (3) ◽  
pp. 35-45 ◽  
Author(s):  
Barry Smyth ◽  
Jill Freyne ◽  
Maurice Coyle ◽  
Peter Briggs
Keyword(s):  
Recommender Systems ◽  
Search Engines ◽  
Web Search ◽  
Online Information ◽  
Information Discovery ◽  
Proactive Approach ◽  
Systems Research ◽  
Traditional Approaches ◽  
New Generation

Recommender systems now play an important role in online information discovery, complementing traditional approaches such as search and navigation, with a more proactive approach to discovery that is informed by the users interests and preferences. To date recommender systems have been deployed within a variety of e-commerce domains, covering a range of products such as books, music, movies, and have proven to be a successful way to convert browsers into buyers. Recommendation technologies have a potentially much greater role to play in information discovery however and in this article we consider recent research that takes a fresh look at web search as a fertile platform for recommender systems research as users demand a new generation of search engines that are less susceptible to manipulation and more responsive to searcher needs and preferences.

scholarly journals MIDV-500: a dataset for identity document analysis and recognition on mobile devices in video stream

2019 ◽  
Vol 43 (5) ◽  
pp. 818-824 ◽  
Author(s):  
V.V. Arlazarov ◽  
K. Bulatov ◽  
T. Chernov ◽  
V.L. Arlazarov
Keyword(s):  
Mobile Devices ◽  
Face Detection ◽  
Data Extraction ◽  
Personal Data ◽  
Ground Truth ◽  
Document Analysis ◽  
Video Stream ◽  
Text Line ◽  
Document Recognition ◽  
Identity Document

A lot of research has been devoted to identity documents analysis and recognition on mobile devices. However, no publicly available datasets designed for this particular problem currently exist. There are a few datasets which are useful for associated subtasks but in order to facilitate a more comprehensive scientific and technical approach to identity document recognition more specialized datasets are required. In this paper we present a Mobile Identity Document Video dataset (MIDV-500) consisting of 500 video clips for 50 different identity document types with ground truth which allows to perform research in a wide scope of document analysis problems. The paper presents characteristics of the dataset and evaluation results for existing methods of face detection, text line recognition, and document fields data extraction. Since an important feature of identity documents is their sensitiveness as they contain personal data, all source document images used in MIDV-500 are either in public domain or distributed under public copyright licenses. The main goal of this paper is to present a dataset. However, in addition and as a baseline, we present evaluation results for existing methods for face detection, text line recognition, and document data extraction, using the presented dataset.

scholarly journals Fairness in rankings and recommendations: an overview

2021 ◽  
Author(s):  
Evaggelia Pitoura ◽  
Kostas Stefanidis ◽  
Georgia Koutrika
Keyword(s):  
Recommender Systems ◽  
Search Engines ◽  
Data Driven ◽  
Sources Of Information ◽  
Future Work

AbstractWe increasingly depend on a variety of data-driven algorithmic systems to assist us in many aspects of life. Search engines and recommender systems among others are used as sources of information and to help us in making all sort of decisions from selecting restaurants and books, to choosing friends and careers. This has given rise to important concerns regarding the fairness of such systems. In this work, we aim at presenting a toolkit of definitions, models and methods used for ensuring fairness in rankings and recommendations. Our objectives are threefold: (a) to provide a solid framework on a novel, quickly evolving and impactful domain, (b) to present related methods and put them into perspective and (c) to highlight open challenges and research paths for future work.

Theorizing Curation

2020 ◽  
Author(s):  
Jenny Davis
Keyword(s):  
Recommender Systems ◽  
Public Life ◽  
Theoretical Construct ◽  
Identity Processes ◽  
Production And Consumption ◽  
Information Studies ◽  
Data Saturation ◽  
Matrix Production

Through a theoretical and substantive review, the author argues that curation is a central thread that weaves together and underlies multiple and diverse elements of personal and public life. This argument is built on a theoretical scaffold which delineates curation as a situated matrix of production and consumption, networks, and code. Defined broadly as the discriminate selection and organization of materials, the author documents curation as it figures into identity processes, content moderation, news and information, and recommender systems. The curatorial matrix (production and consumption, networks and code) ties together distinct literatures from across internet and information studies. This places scholars in conversation with each other and demonstrates curation as a foundational process in an environment marked by data saturation. The author first outlines curation as a theoretical construct and then reviews select works, rooting them in the curatorial matrix.

Video Content-Based Retrieval

2011 ◽  
pp. 3965-3969
Author(s):  
Waleed E. Farag
Keyword(s):  
Search Engines ◽  
Multimedia Applications ◽  
Multimedia Data ◽  
Video Content ◽  
Background Current ◽  
Research Directions ◽  
Content Based Retrieval ◽  
Monotonic Increase ◽  
Processing Power ◽  
Media Data

Recently, multimedia applications have undergone explosive growth due to the monotonic increase in the available processing power and bandwidth. This incurs the generation of large amounts of media data that need to be effectively and efficiently organized and stored. While these applications generate and use vast amounts of multimedia data, the technologies for organizing and searching them are still immature. These data are usually stored in multimedia archives utilizing search engines to enable users to retrieve the required information. In this article, each of the above stages will be reviewed and expounded. Background, current research directions, and outstanding problems will also be discussed.

Navigating Multimedia

2013 ◽  
pp. 11-26 ◽  
Author(s):  
Julie A. DeCesare
Keyword(s):  
Search Engines ◽  
Multimedia Content ◽  
Video Content ◽  
Visual Content ◽  
Research Strategies ◽  
Content Quality ◽  
Content Search ◽  
Subject Specific ◽  
Technical Specifications ◽  
The Web

The Web has quickly become a resource for multimedia and video content. Search engines have tools to mine for visual content, but finding video content creates different challenges than searching for text. This chapter presents a detailed guide on searching for visual multimedia content and provides a showcase of innovative collections and resources. The reader will learn research strategies, gain specific skills in navigating multimedia, and receive a list of resources for finding subject-specific and interdisciplinary video content. Resources are reviewed based on content quality, partnerships, technical specifications, and overall usability.

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