Title
Automated textual descriptions for a wide range of video events with 48 human actions
Abstract
Presented is a hybrid method to generate textual descriptions of video based on actions. The method includes an action classifier and a description generator. The aim for the action classifier is to detect and classify the actions in the video, such that they can be used as verbs for the description generator. The aim of the description generator is (1) to find the actors (objects or persons) in the video and connect these correctly to the verbs, such that these represent the subject, and direct and indirect objects, and (2) to generate a sentence based on the verb, subject, and direct and indirect objects. The novelty of our method is that we exploit the discriminative power of a bag-of-features action detector with the generative power of a rule-based action descriptor. Shown is that this approach outperforms a homogeneous setup with the rule-based action detector and action descriptor.
Year
DOI
Venue
2012
10.1007/978-3-642-33863-2_37
ECCV Workshops (1)
Keywords
Field
DocType
description generator,hybrid method,human action,discriminative power,textual description,rule-based action detector,automated textual description,indirect object,bag-of-features action detector,wide range,action descriptor,video event,rule-based action descriptor,action classifier,informatics
Verb,Computer vision,Pattern recognition,Homogeneous,Computer science,Exploit,Artificial intelligence,Novelty,Classifier (linguistics),Sentence,Detector,Discriminative model
Conference
Volume
ISSN
Citations 
7583
0302-9743
12
PageRank 
References 
Authors
0.71
15
3
Name
Order
Citations
PageRank
Patrick Hanckmann1232.89
Klamer Schutte217318.26
Gertjan J. Burghouts367930.31