Abstract
We propose a new generative model, and a new image similarity kernel based on a linked hierarchy of probabilistic segmentations. The model is used to efficiently segment multiple images into a consistent set of image regions. The segmentations are provided at several levels of granularity and links among them are automatically provided. Model training and inference in it is faster than most local feature extraction algorithms, and yet the provided image segmentation, and the segment matching among images provide a rich backdrop for image recognition, segmentation and registration tasks. © 2010 Springer-Verlag.
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CITATION STYLE
Perina, A., Jojic, N., Castellani, U., Cristani, M., & Murino, V. (2010). Object recognition with hierarchical stel models. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6316 LNCS, pp. 15–28). Springer Verlag. https://doi.org/10.1007/978-3-642-15567-3_2
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