Video temporal alignment for object viewpoint

Anestis Papazoglou, Luca Del Pero, Vittorio Ferrari

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


We address the problem of temporally aligning semantically similar videos, for example two videos of cars on different tracks. We present an alignment method that establishes frame-to-frame correspondences such that the two cars are seen from a similar viewpoint (e.g. facing right), while also being temporally smooth and visually pleasing. Unlike previous works, we do not assume that the videos show the same scripted sequence of events. We compare against three alternative methods, including the popular DTW algorithm, on a new dataset of realistic videos collected from the internet. We perform a comprehensive evaluation using a novel protocol that includes both quantitative measures and a user study on visual pleasingness.
Original languageEnglish
Title of host publicationThe 13th Asian Conference on Computer Vision (ACCV 2016)
PublisherSpringer, Cham
Number of pages16
ISBN (Electronic)978-3-319-54190-7
ISBN (Print)978-3-319-54189-1
Publication statusPublished - 12 Mar 2017
Event13th Asian Conference on Computer Vision - Taipei, Taiwan, Province of China
Duration: 20 Nov 201624 Nov 2016

Publication series

NameLecture Notes in Computer Science
PublisherSpringer, Cham
ISSN (Print)0302-9743


Conference13th Asian Conference on Computer Vision
Abbreviated titleACCV'16
Country/TerritoryTaiwan, Province of China
Internet address


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