A new trajectory based motion segmentation benchmark dataset (UdG-MS15)

Muhammad Habib Mahmood, Luca Zappella, Yago Díez, Joaquim Salvi, Xavier Lladó

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)


Motion segmentation (MS) is an essential step in video analysis. Its quantitative and qualitative evaluation is largely dependent on the dataset used for testing. Although there are publicly available datasets such as Hopkins and FBMS, they have limitations in terms of number of motions, partial/complete occlusion, stopping motion, sequence length, and real life natural sequences. Due to these limitations, many recent proposals have reached nearly zero misclassification, especially for Hopkins, which leaves no room for quantitatively differentiating among proposals. In this paper, we present a new challenging trajectory based MS dataset of 15 sequences, where number of motions and sequence length have been largely increased as compared to the state of the art. An effort has been made to include all forms of distortions that are present in real life scenes. As a starting point, a preliminary benchmark evaluation using a recent and well known state of the art algorithm has been provided for this dataset.

Original languageEnglish
Title of host publicationPattern Recognition and Image Analysis - 7th Iberian Conference, IbPRIA 2015, Proceedings
EditorsJaime S. Cardoso, Roberto Paredes, Xosé M. Pardo
PublisherSpringer Verlag
Number of pages8
ISBN (Electronic)9783319193892
Publication statusPublished - 2015
Event7th Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA 2015 - Santiago de Compostela, Spain
Duration: 2015 Jun 172015 Jun 19

Publication series

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


Other7th Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA 2015
CitySantiago de Compostela


  • Benchmark
  • Dataset
  • Motion segmentation
  • Tracking
  • Trajectory

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)


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