Babytalk : understanding and generating simple image descriptions

We present a system to automatically generate natural language descriptions from images. This system consists of two parts. The first part, content planning, smooths the output of computer vision-based detection and recognition algorithms with statistics mined from large pools of visually descriptiv...

Ausführliche Beschreibung

Bibliographische Detailangaben
Veröffentlicht in:IEEE transactions on pattern analysis and machine intelligence. - 1979. - 35(2013), 12 vom: 01. Dez., Seite 2891-903
1. Verfasser: Kulkarni, Girish (VerfasserIn)
Weitere Verfasser: Premraj, Visruth, Ordonez, Vicente, Dhar, Sagnik, Li, Siming, Choi, Yejin, Berg, Alexander C, Berg, Tamara L
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2013
Zugriff auf das übergeordnete Werk:IEEE transactions on pattern analysis and machine intelligence
Schlagworte:Journal Article Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S.
Beschreibung
Zusammenfassung:We present a system to automatically generate natural language descriptions from images. This system consists of two parts. The first part, content planning, smooths the output of computer vision-based detection and recognition algorithms with statistics mined from large pools of visually descriptive text to determine the best content words to use to describe an image. The second step, surface realization, chooses words to construct natural language sentences based on the predicted content and general statistics from natural language. We present multiple approaches for the surface realization step and evaluate each using automatic measures of similarity to human generated reference descriptions. We also collect forced choice human evaluations between descriptions from the proposed generation system and descriptions from competing approaches. The proposed system is very effective at producing relevant sentences for images. It also generates descriptions that are notably more true to the specific image content than previous work
Beschreibung:Date Completed 22.04.2016
Date Revised 02.12.2018
published: Print
Citation Status MEDLINE
ISSN:1939-3539