Natural Language Descriptions for Human Activities in Video Streams

Nouf Alharbi, Yoshihiko Gotoh


Abstract
There has been continuous growth in the volume and ubiquity of video material. It has become essential to define video semantics in order to aid the searchability and retrieval of this data. We present a framework that produces textual descriptions of video, based on the visual semantic content. Detected action classes rendered as verbs, participant objects converted to noun phrases, visual properties of detected objects rendered as adjectives and spatial relations between objects rendered as prepositions. Further, in cases of zero-shot action recognition, a language model is used to infer a missing verb, aided by the detection of objects and scene settings. These extracted features are converted into textual descriptions using a template-based approach. The proposed video descriptions framework evaluated on the NLDHA dataset using ROUGE scores and human judgment evaluation.
Anthology ID:
W17-3512
Volume:
Proceedings of the 10th International Conference on Natural Language Generation
Month:
September
Year:
2017
Address:
Santiago de Compostela, Spain
Venues:
INLG | WS
SIG:
SIGGEN
Publisher:
Association for Computational Linguistics
Note:
Pages:
85–94
Language:
URL:
https://www.aclweb.org/anthology/W17-3512
DOI:
10.18653/v1/W17-3512
Bib Export formats:
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PDF:
http://aclanthology.lst.uni-saarland.de/W17-3512.pdf