Abstract
This paper presents a new approach to the problem of simultaneous location and segmentation of object in images. The main emphasis is done on the information provided by the contour fragments present in the image. Clusters of contour fragments are created in order to represent the labels defining the different parts of the object. An unordered probabilistic graph is used to model the objects, where a greedy approach (using dynamic programming) is used to fit the graph model to the labels.
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Marín-Jiménez, M.J., de la Blanca, N.P., Gómez, J.I. (2007). Locating and Segmenting 3D Deformable Objects by Using Clusters of Contour Fragments. In: Martí, J., Benedí, J.M., Mendonça, A.M., Serrat, J. (eds) Pattern Recognition and Image Analysis. IbPRIA 2007. Lecture Notes in Computer Science, vol 4477. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72847-4_52
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DOI: https://doi.org/10.1007/978-3-540-72847-4_52
Publisher Name: Springer, Berlin, Heidelberg
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