TY - GEN
T1 - Visual object detection by specifying the scale and rotation transformations
AU - Sato, Yasuomi D.
AU - Jitsev, Jenia
AU - Von Der Malsburg, Christoph
N1 - Copyright:
Copyright 2011 Elsevier B.V., All rights reserved.
PY - 2010
Y1 - 2010
N2 - We here propose a simple but highly potential algorithm to detect a model object's position on an input image by determining the initially unknown transformational states of the model object, in particular, size and 2D-rotation. In this algorithm, a single feature is extracted around or at the center of the input image through 2D-Gabor wavelet transformation, in order to find not only the most likely relative size and rotation to the model object, but also the most appropriate positional region on the input image for detecting the correct relative transformational states. We also show the reliable function on the face images of different persons, or of different appearance in the same person.
AB - We here propose a simple but highly potential algorithm to detect a model object's position on an input image by determining the initially unknown transformational states of the model object, in particular, size and 2D-rotation. In this algorithm, a single feature is extracted around or at the center of the input image through 2D-Gabor wavelet transformation, in order to find not only the most likely relative size and rotation to the model object, but also the most appropriate positional region on the input image for detecting the correct relative transformational states. We also show the reliable function on the face images of different persons, or of different appearance in the same person.
KW - Feature Correspondence
KW - Gabor Filter Decomposition
KW - Transformation Specific Similarities
KW - Visual Object Detection
UR - http://www.scopus.com/inward/record.url?scp=78650224117&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=78650224117&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-17534-3_76
DO - 10.1007/978-3-642-17534-3_76
M3 - Conference contribution
AN - SCOPUS:78650224117
SN - 3642175333
SN - 9783642175336
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 616
EP - 624
BT - Neural Information Processing
T2 - 17th International Conference on Neural Information Processing, ICONIP 2010
Y2 - 22 November 2010 through 25 November 2010
ER -