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Title: EQUI-VOCAL: Synthesizing Queries for Compositional Video Events from Limited User Interactions
We introduce EQUI-VOCAL: a new system that automatically synthesizes queries over videos from limited user interactions. The user only provides a handful of positive and negative examples of what they are looking for. EQUI-VOCAL utilizes these initial examples and additional ones collected through active learning to efficiently synthesize complex user queries. Our approach enables users to find events without database expertise, with limited labeling effort, and without declarative specifications or sketches. Core to EQUI-VOCAL's design is the use of spatio-temporal scene graphs in its data model and query language and a novel query synthesis approach that works on large and noisy video data. Our system outperforms two baseline systems---in terms of F1 score, synthesis time, and robustness to noise---and can flexibly synthesize complex queries that the baselines do not support.  more » « less
Award ID(s):
2211133
PAR ID:
10531462
Author(s) / Creator(s):
; ; ; ; ;
Publisher / Repository:
VLDB Endowment
Date Published:
Journal Name:
Proceedings of the VLDB Endowment
Volume:
16
Issue:
11
ISSN:
2150-8097
Page Range / eLocation ID:
2714 to 2727
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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