Abstract
We present a method for 3D object modeling and recognition which is robust to scale and illumination changes, and to viewpoint variations. The object model is derived from the local features extracted and tracked on an image sequence of the object. The recognition phase is based on an SVM classifier. We analyse in depth all the crucial steps of the method, and report very promising results on a dataset of 11 objects, that show how the method is also tolerant to occlusions and moderate scene clutter.
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© 2006 Springer-Verlag Berlin Heidelberg
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Delponte, E., Arnaud, E., Odone, F., Verri, A. (2006). Analysis on a Local Approach to 3D Object Recognition. In: Franke, K., Müller, KR., Nickolay, B., Schäfer, R. (eds) Pattern Recognition. DAGM 2006. Lecture Notes in Computer Science, vol 4174. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11861898_26
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DOI: https://doi.org/10.1007/11861898_26
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-44412-1
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