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Conference Paper ActionNet-VE Dataset: A Dataset for Describing Visual Events by Extending VIRAT Ground 2.0
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Authors
Jinyoung Moon, Yongjin Kwon, Kyuchang Kang, Jongyoul Park
Issue Date
2015-11
Citation
International Conference on Signal Processing, Image Processing and Pattern Recognition (SIP) 2015, pp.1-4
Language
English
Type
Conference Paper
DOI
https://dx.doi.org/10.1109/SIP.2015.9
Project Code
15MS4500, Development of High Performance Visual BigData Discovery Platform, Park Kyoung
Abstract
This paper introduces a dataset for recognizing and describing interactive events between objects of interest including persons, cars, bikes, and carried objects. Although there have been many video datasets for human activity recognition, most of them focus on persons and their actions and sometimes ignore the specific information on related objects, such as their object type and minimum bounding boxes, in annotations. ActionNet-VE dataset was designed to include full annotations on all objects and events of interest occurred in a video clip for describing the semantics of the event. The dataset adopt 75 video clips from VIRAT Ground 2.0, and extend annotations on the events and their related objects. In addition, the dataset describes semantics of each events by using elements of sentences, such as verb, subject, and objects.
KSP Keywords
Bounding Box, Human activity recognition(HAR), Video clips, interactive events, visual events