Learning from Narrated Instruction Videos
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21730%2F18%3A00318985" target="_blank" >RIV/68407700:21730/18:00318985 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1109/TPAMI.2017.2749223" target="_blank" >http://dx.doi.org/10.1109/TPAMI.2017.2749223</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/TPAMI.2017.2749223" target="_blank" >10.1109/TPAMI.2017.2749223</a>
Alternative languages
Result language
angličtina
Original language name
Learning from Narrated Instruction Videos
Original language description
Automatic assistants could guide a person or a robot in performing new tasks, such as changing a car tire or repotting a plant. Creating such assistants, however, is non-trivial and requires understanding of visual and verbal content of a video. Towards this goal, we here address the problem of automatically learning the main steps of a task from a set of narrated instruction videos. We develop a new unsupervised learning approach that takes advantage of the complementary nature of the input video and the associated narration. The method sequentially clusters textual and visual representations of a task, where the two clustering problems are linked by joint constraints to obtain a single coherent sequence of steps in both modalities. To evaluate our method, we collect and annotate a new challenging dataset of real-world instruction videos from the Internet. The dataset contains videos for five different tasks with complex interactions between people and objects, captured in a variety of indoor and outdoor settings. We experimentally demonstrate that the proposed method can automatically discover, learn and localize the main steps of a task input videos.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/EF15_003%2F0000468" target="_blank" >EF15_003/0000468: Intelligent Machine Perception</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
IEEE Transactions on Pattern Analysis and Machine Intelligence
ISSN
0162-8828
e-ISSN
1939-3539
Volume of the periodical
40
Issue of the periodical within the volume
9
Country of publishing house
US - UNITED STATES
Number of pages
15
Pages from-to
2194-2208
UT code for WoS article
000440868400012
EID of the result in the Scopus database
2-s2.0-85029154712