HAVIC MED Training Data -- Videos, Metadata and Annotation

Item Name: HAVIC MED Training Data -- Videos, Metadata and Annotation
Author(s): Amanda Morris, Stephanie Strassel, Xuansong Li, Brian Antonishek, Jonathan G. Fiscus
LDC Catalog No.: LDC2021V01
ISBN: 1-58563-982-6
ISLRN: 265-481-756-640-8
DOI: https://doi.org/10.35111/rak4-xf36
Release Date: December 15, 2021
Member Year(s): 2021
DCMI Type(s): MovingImage, Text
Data Source(s): web collection
Project(s): HAVIC
Application(s): event detection
Language(s): English
Language ID(s): eng
Online Documentation: LDC2021V01 Documents
Licensing Instructions: Subscription & Standard Members, and Non-Members
Citation: Morris, Amanda, et al. HAVIC MED Training Data -- Videos, Metadata and Annotation LDC2021V01. Web Download. Philadelphia: Linguistic Data Consortium, 2021.
Related Works: View

Introduction

HAVIC MED Training Data -- Videos, Metadata and Annotation was developed by the Linguistic Data Consortium (LDC) and is comprised of approximately 2,100 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 Training Data is a subset of that corpus, specifically, a collection of event and background videos for the HAVIC project originally released to support the 2011, 2012, 2013, 2014, and 2015 Multimedia Event Detection tasks.

Data

The data consists of videos representing 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 and annotation sample

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.

Available Media

View Fees





Login for the applicable fee