oai:www.ldc.upenn.edu:LDC2022V02
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OLAC Record oai:www.ldc.upenn.edu:LDC2022V02 |
| Metadata | ||
| Title: | HAVIC MED Novel 2 Test -- Videos, Metadata and Annotation | |
| Access Rights: | Licensing Instructions for Subscription & Standard Members, and Non-Members: http://www.ldc.upenn.edu/language-resources/data/obtaining | |
| Bibliographic Citation: | Li, Xuansong, et al. HAVIC MED Novel 2 Test -- Videos, Metadata and Annotation LDC2022V02. Web Download. Philadelphia: Linguistic Data Consortium, 2022 | |
| Contributor: | Li, Xuansong | |
| Strassel, Stephanie | ||
| Jones, Karen | ||
| Antonishek, Brian | ||
| Fiscus, Jonathan G. | ||
| Date (W3CDTF): | 2022 | |
| Date Issued (W3CDTF): | 2022-08-15 | |
| Description: | *Introduction* HAVIC MED Novel 2 Test -- Videos, Metadata and Annotation was developed by the Linguistic Data Consortium (LDC) and is comprised of approximately 6,200 hours of user-generated videos with annotation and metadata. To advance multimodal event detection and related technologies, LDC developed, in collaboration with NIST (the National Institute of Standards and Technology), a large, heterogeneous, annotated multimodal corpus for HAVIC (the Heterogeneous Audio Visual Internet Collection) that was used in the NIST-sponsored MED (Multimedia Event Detection) task for several years. HAVIC MED Novel 2 Test is a subset of that corpus, specifically, a collection of videos, metadata and annotation for the HAVIC project originally released to support the 2015 Multimedia Event Detection tasks. *Data* The data consists of videos of various events (event videos) and videos completely unrelated to events (background videos) harvested by a large team of human annotators. Each event video was manually annotated with a set of judgments describing its event properties and other salient features. Background videos were labeled with topic and genre categories. All video files are in .mp4 format (h.264), with varying bit-rates and levels of audio fidelity and video resolution. Metadata and annotation for the videos are stored in a .tsv file. *Samples* Please view this video sample (MP4). *Updates* None at this time. *Additional Licensing Instructions* This 'members-only' corpus is available to current members. Contact ldc@ldc.upenn.edu for information about becoming a member. | |
| Extent: | Corpus size: 1610038355 KB | |
| Identifier: | LDC2022V02 | |
| https://catalog.ldc.upenn.edu/LDC2022V02 | ||
| ISBN: 1-58563-997-4 | ||
| ISLRN: 216-328-718-009-3 | ||
| DOI: 10.35111/85d3-zz16 | ||
| Language: | English | |
| Language (ISO639): | eng | |
| Medium: | Distribution: Web Download | |
| Publisher: | Linguistic Data Consortium | |
| Publisher (URI): | https://www.ldc.upenn.edu | |
| Relation (URI): | https://catalog.ldc.upenn.edu/docs/LDC2022V02 | |
| Rights Holder: | Portions © 2011-2016 YouTube, LLC, © 2011-2016, 2022 Trustees of the University of Pennsylvania | |
| Type (DCMI): | MovingImage | |
| Text | ||
| Type (OLAC): | primary_text | |
OLAC Info |
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| Archive: | The LDC Corpus Catalog | |
| Description: | http://www.language-archives.org/archive/www.ldc.upenn.edu | |
| GetRecord: | OAI-PMH request for OLAC format | |
| GetRecord: | Pre-generated XML file | |
OAI Info |
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| OaiIdentifier: | oai:www.ldc.upenn.edu:LDC2022V02 | |
| DateStamp: | 2023-01-10 | |
| GetRecord: | OAI-PMH request for simple DC format | |
Search Info | ||
| Citation: | Li, Xuansong; Strassel, Stephanie; Jones, Karen; Antonishek, Brian; Fiscus, Jonathan G. 2022. Linguistic Data Consortium. | |
| Terms: | area_Europe country_GB dcmi_MovingImage dcmi_Text iso639_eng olac_primary_text | |