IPSJ Transactions on Computer Vision and Applications
Online ISSN : 1882-6695
ISSN-L : 1882-6695
Distance Computation Between Binary Code and Real Vector for Efficient Keypoint Matching
Yuji YamauchiMitsuru AmbaiIkuro SatoYuichi YoshidaHironobu Fujiyoshi
Author information

2013 Volume 5 Pages 124-128


Image recognition in client server system has a problem of data traffic. However, reducing data traffic gives rise to worsening of performance. Therefore, we represent binary codes as high dimensional local features in client side, and represent real vectors in server side. As a result, we can suppress the worsening of the performance, but it problems of an increase in the computational cost of the distance computation and a different scale of norm between feature vectors. Therefore, to solve the first problem, we optimize the scale factor so as to absorb the scale difference of Euclidean norm. For second problem, we compute efficiently the Euclidean distance by decomposing the real vector into weight factors and binary basis vectors. As a result, the proposed method achieves the keypoint matching with high-speed and high-precision even if the data traffic was reduced.

Information related to the author
© 2013 by the Information Processing Society of Japan
Previous article Next article