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Abstract
In this paper a robust method is presented to classify and estimate an objects pose from a real time range image and a low dimensional model. The model is made from a range image training set which is reduced dimensionally by a nonlinear manifold learning method named Local Linear Embedding (LLE). New range images are then projected to this model giving the low dimensional coordinates of the object pose in an efficient manner. The range images are acquired by a state of the art SwissRanger SR-3000 camera making the projection process work in real-time.
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Technical University of Denmark, Informatics and Mathematical Modelling, Building 321, Richard Petersens Plads, DTU DK-2800 Kgs. Lyngby,
Sigurjón Árni Guðmundsson, Rasmus Larsen & Bjarne K. Ersbøll
- Sigurjón Árni Guðmundsson
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- Rasmus Larsen
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- Bjarne K. Ersbøll
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Guðmundsson, S.Á., Larsen, R., Ersbøll, B.K. (2007). Robust Pose Estimation Using the SwissRanger SR-3000 Camera. In: Ersbøll, B.K., Pedersen, K.S. (eds) Image Analysis. SCIA 2007. Lecture Notes in Computer Science, vol 4522. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73040-8_98
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