TY - JOUR
T1 - The wordometer - Estimating the number of words read using document image retrieval and mobile eye tracking
AU - Kunze, Kai
AU - Kawaichi, Hitoshi
AU - Yoshimura, Kazuyo
AU - Kise, Koichi
PY - 2013
Y1 - 2013
N2 - We introduce the Wordometer, a novel method to estimate the number of words a user reads using a mobile eye tracker and document image retrieval. We present a reading detection algorithm which works with over 91 % accuracy over 10 test subjects using 10-fold cross validation. We implement two algorithms to estimate the read words using a line break detector. A simple version gives an average error rate of 13,5 % for 9 users over 10 documents. A more sophisticated word count algorithm based on support vector regression with an RBF kernel reaches an average error rate from only 8.2 % (6.5 % if one test subject with abnormal behavior is excluded). The achieved error rates are comparable to pedometers that count our steps in our daily life. Thus, we believe the Wordometer can be used as a step counter for the information we read to make our knowledge life healthier.
AB - We introduce the Wordometer, a novel method to estimate the number of words a user reads using a mobile eye tracker and document image retrieval. We present a reading detection algorithm which works with over 91 % accuracy over 10 test subjects using 10-fold cross validation. We implement two algorithms to estimate the read words using a line break detector. A simple version gives an average error rate of 13,5 % for 9 users over 10 documents. A more sophisticated word count algorithm based on support vector regression with an RBF kernel reaches an average error rate from only 8.2 % (6.5 % if one test subject with abnormal behavior is excluded). The achieved error rates are comparable to pedometers that count our steps in our daily life. Thus, we believe the Wordometer can be used as a step counter for the information we read to make our knowledge life healthier.
KW - document image retrival
KW - eye gaze
KW - eyetracking
KW - word count
KW - wordometer
UR - http://www.scopus.com/inward/record.url?scp=84889599875&partnerID=8YFLogxK
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U2 - 10.1109/ICDAR.2013.14
DO - 10.1109/ICDAR.2013.14
M3 - Conference article
AN - SCOPUS:84889599875
SP - 25
EP - 29
JO - Proceedings of the International Conference on Document Analysis and Recognition, ICDAR
JF - Proceedings of the International Conference on Document Analysis and Recognition, ICDAR
SN - 1520-5363
M1 - 6628579
T2 - 12th International Conference on Document Analysis and Recognition, ICDAR 2013
Y2 - 25 August 2013 through 28 August 2013
ER -