SCENE TEXT RECOGNITION IN MULTIPLE FRAMES BASED ON TEXT TRACKING

被引：0

作者：

Rong, Xuejian ^{[1
]}

Yi, Chucai ^{[2
]}

Yang, Xiaodong ^{[1
]}

Tian, Yingli ^{[1
,2
]}

机构：

[1] CUNY City Coll, New York, NY 10031 USA

[2] CUNY, Grad Ctr, New York, NY USA

来源：

2014 IEEE INTERNATIONAL CONFERENCE ON MULTIMEDIA AND EXPO (ICME) | 2014年

关键词：

Scene text recognition; text tracking; feature representation of scene text character; Fisher Vector; video dataset of scene text;

D O I：

暂无

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

Text signage as visual indicators in natural scene plays an important role in navigation and notification in our daily life. Most previous methods of scene text extraction are developed from a single scene image. In this paper, we propose a multi-frame based scene text recognition method by tracking text regions in a video captured by a moving camera. The main contributions of this paper are as follows. First, we present a framework of scene text recognition in multiple frames based on feature representation of scene text character (STC) for character prediction and conditional random field (CRF) model for word configuration. Second, a feature representation of STC is employed from dense sampled SIFT descriptors and Fisher Vector. Third, we collect a dataset for text information extraction from natural scene videos. Our proposed multi-frame scene text recognition is more compatible with image/video-based mobile applications. The experimental results demonstrate that STC prediction and word configuration in multiple frames based on text tracking significantly improves the performance of scene text recognition.

引用

页数：6