@inproceedings{39fa6fb01fbb4c8483983dc9249ce330,
title = "Segmentation-free keyword spotting framework using dynamic background model",
abstract = "We propose a segmentation free word spotting framework using Dynamic Background Model. The proposed approach is an extension to our previous work where dynamic background model was introduced and integrated with a segmentation based recognizer for keyword spotting. The dynamic background model uses the local character matching scores and global word level hypotheses scores to separate keywords from non-keywords. We integrate and evaluate this model on Hidden Markov Model (HMM) based segmentation free recognizer which works at line level without any need for word segmentation. We outperform the state of the art line level word spotting system on IAM dataset.",
keywords = "Dynamic Background Model, Hidden Markov Model, Keyword Spotting",
author = "Gaurav Kumar and Safwan Wshah and Venu Govindaraju and Sitaram Ramachandrula",
year = "2013",
doi = "10.1117/12.2008597",
language = "English",
isbn = "9780819494313",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
booktitle = "Proceedings of SPIE-IS and T Electronic Imaging - Document Recognition and Retrieval XX",
note = "Document Recognition and Retrieval XX ; Conference date: 05-02-2013 Through 07-02-2013",
}