Title :
The benefits and challenges of collecting richer object annotations
Author :
Endres, Ian ; Farhadi, Ali ; Hoiem, Derek ; Forsyth, David A.
Author_Institution :
Dept. of Comput. Sci., Univ. of Illinois Urbana Champaign, Champaign, IL, USA
Abstract :
Several recent works have explored the benefits of providing more detailed annotations for object recognition. These annotations provide information beyond object names, and allow a detector to reason and describe individual instances in plain English. However, by demanding more specific details from annotators, new difficulties arise, such as stronger language dependencies and limited annotator attention. In this work, we present the challenges of constructing such a detailed dataset, and discuss why the benefits of using this data outweigh the difficulties of collecting it.
Keywords :
object recognition; annotator attention; language dependencies; object annotations; object recognition; Computer science; Costs; Detectors; Face recognition; Humans; Natural languages; Object detection; Object recognition; Robots; Yarn;
Conference_Titel :
Computer Vision and Pattern Recognition Workshops (CVPRW), 2010 IEEE Computer Society Conference on
Conference_Location :
San Francisco, CA
Print_ISBN :
978-1-4244-7029-7
DOI :
10.1109/CVPRW.2010.5543183