Abstract
We present a new approach to recognize 3D objects in an image taking the available information in it. To reach this aim a method based on a two step algorithm will be developed. In the first step, each 3D model will be converted in a set of 2D images using an aspect graph algorithm in which the concept of visual event is defined as the moment when the projective invariants got from the model have changed. In the second step, we use these invariants to recognize the object situated in the scene. The main contribution to this work is the combination of two typical techniques used to object recognition like are aspect graph and projective invariants. We have obtained better results with this combinations than by using them separately.
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© 2004 Springer-Verlag Berlin Heidelberg
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González, J.M., Sebastián, J.M., García, D., Sánchez, F., Angel, L. (2004). Recognition of 3D Object from One Image Based on Projective and Permutative Invariants. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2004. Lecture Notes in Computer Science, vol 3211. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30125-7_87
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DOI: https://doi.org/10.1007/978-3-540-30125-7_87
Publisher Name: Springer, Berlin, Heidelberg
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