Perfect Match in Video Retrieval

Sebastian Lubos*, Massimiliano Rubino, Christian Tautschnig, Markus Tautschnig, Boda Wen, Klaus Schoeffmann, Alexander Felfernig

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review

Abstract

This paper presents the first version of our video search system Perfect Match for the Video Browser Showdown 2023 competition. The system indexes videos from the large V3C video dataset and derives visual content descriptors automatically. Furthermore, it provides an interactive video search user interface (UI), which implements approaches from the domain of critiquing-based recommendation, to enable the user to find the desired video segment as fast as possible.

Original languageEnglish
Title of host publicationMultiMedia Modeling - 29th International Conference, MMM 2023, Proceedings
EditorsDuc-Tien Dang-Nguyen, Cathal Gurrin, Alan F. Smeaton, Martha Larson, Stevan Rudinac, Minh-Son Dao, Christoph Trattner, Phoebe Chen
Pages634-639
Number of pages6
DOIs
Publication statusPublished - 2023

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13833 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Keywords

  • Critiquing
  • Interactive video search
  • Video retrieval

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

Fingerprint

Dive into the research topics of 'Perfect Match in Video Retrieval'. Together they form a unique fingerprint.

Cite this