TY - GEN
T1 - On-line document registering and retrieving system for AR annotation overlay
AU - Uchiyama, Hideaki
AU - Pilet, Julien
AU - Saito, Hideo
PY - 2010
Y1 - 2010
N2 - We propose a system that registers and retrieves text documents to annotate them on-line. The user registers a text document captured from a nearly top view and adds virtual annotations. When the user thereafter captures the document again, the system retrieves and displays the appropriate annotations, in real-time and at the correct location. Registering and deleting documents is done by user interaction. Our approach relies on LLAH, a hashing based method for document image retrieval. At the on-line registering stage, our system extracts keypoints from the input image and stores their descriptors computed from their neighbors. After registration, our system can quickly find the stored document corresponding to an input view by matching keypoints. From the matches, our system estimates the geometrical relationship between the camera and the document for accurately overlaying the annotations. In the experimental results, we show that our system can achieve on-line and real-time performances.
AB - We propose a system that registers and retrieves text documents to annotate them on-line. The user registers a text document captured from a nearly top view and adds virtual annotations. When the user thereafter captures the document again, the system retrieves and displays the appropriate annotations, in real-time and at the correct location. Registering and deleting documents is done by user interaction. Our approach relies on LLAH, a hashing based method for document image retrieval. At the on-line registering stage, our system extracts keypoints from the input image and stores their descriptors computed from their neighbors. After registration, our system can quickly find the stored document corresponding to an input view by matching keypoints. From the matches, our system estimates the geometrical relationship between the camera and the document for accurately overlaying the annotations. In the experimental results, we show that our system can achieve on-line and real-time performances.
KW - LLAH
KW - Poes estimation
KW - augmented reality
KW - document retrieval
KW - feature matching
UR - http://www.scopus.com/inward/record.url?scp=77954487840&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77954487840&partnerID=8YFLogxK
U2 - 10.1145/1785455.1785478
DO - 10.1145/1785455.1785478
M3 - Conference contribution
AN - SCOPUS:77954487840
SN - 9781605588254
T3 - ACM International Conference Proceeding Series
BT - Proceedings of the 1st Augmented Human International Conference, AH '10
T2 - 1st Augmented Human International Conference, AH'10
Y2 - 2 April 2010 through 3 April 2010
ER -