[{"date_published":"2007-06-15T00:00:00Z","year":"2007","language":[{"iso":"eng"}],"oa_version":"None","article_processing_charge":"No","alternative_title":["LNCS"],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","day":"15","publication":"First International Conference on Scale Space and Variational Methods in Computer Vision","scopus_import":"1","quality_controlled":"1","status":"public","_id":"18336","citation":{"mla":"Bronstein, Alex M., et al. “Paretian Similarity for Partial Comparison of Non-Rigid Objects.” <i>First International Conference on Scale Space and Variational Methods in Computer Vision</i>, vol. 4485, Springer Nature, 2007, pp. 264–75, doi:<a href=\"https://doi.org/10.1007/978-3-540-72823-8_23\">10.1007/978-3-540-72823-8_23</a>.","ista":"Bronstein AM, Bronstein MM, Bruckstein AM, Kimmel R. 2007. Paretian similarity for partial comparison of non-rigid objects. First International Conference on Scale Space and Variational Methods in Computer Vision. SSVM: Scape Space and Variational Methods in Computer Vision, LNCS, vol. 4485, 264–275.","apa":"Bronstein, A. M., Bronstein, M. M., Bruckstein, A. M., &#38; Kimmel, R. (2007). Paretian similarity for partial comparison of non-rigid objects. In <i>First International Conference on Scale Space and Variational Methods in Computer Vision</i> (Vol. 4485, pp. 264–275). Ischia, Italy: Springer Nature. <a href=\"https://doi.org/10.1007/978-3-540-72823-8_23\">https://doi.org/10.1007/978-3-540-72823-8_23</a>","ama":"Bronstein AM, Bronstein MM, Bruckstein AM, Kimmel R. Paretian similarity for partial comparison of non-rigid objects. In: <i>First International Conference on Scale Space and Variational Methods in Computer Vision</i>. Vol 4485. Springer Nature; 2007:264-275. doi:<a href=\"https://doi.org/10.1007/978-3-540-72823-8_23\">10.1007/978-3-540-72823-8_23</a>","short":"A.M. Bronstein, M.M. Bronstein, A.M. Bruckstein, R. Kimmel, in:, First International Conference on Scale Space and Variational Methods in Computer Vision, Springer Nature, 2007, pp. 264–275.","ieee":"A. M. Bronstein, M. M. Bronstein, A. M. Bruckstein, and R. Kimmel, “Paretian similarity for partial comparison of non-rigid objects,” in <i>First International Conference on Scale Space and Variational Methods in Computer Vision</i>, Ischia, Italy, 2007, vol. 4485, pp. 264–275.","chicago":"Bronstein, Alex M., Michael M. Bronstein, Alfred M. Bruckstein, and Ron Kimmel. “Paretian Similarity for Partial Comparison of Non-Rigid Objects.” In <i>First International Conference on Scale Space and Variational Methods in Computer Vision</i>, 4485:264–75. Springer Nature, 2007. <a href=\"https://doi.org/10.1007/978-3-540-72823-8_23\">https://doi.org/10.1007/978-3-540-72823-8_23</a>."},"date_created":"2024-10-15T11:20:54Z","author":[{"id":"58f3726e-7cba-11ef-ad8b-e6e8cb3904e6","first_name":"Alexander","orcid":"0000-0001-9699-8730","full_name":"Bronstein, Alexander","last_name":"Bronstein"},{"full_name":"Bronstein, Michael M.","first_name":"Michael M.","last_name":"Bronstein"},{"last_name":"Bruckstein","first_name":"Alfred M.","full_name":"Bruckstein, Alfred M."},{"first_name":"Ron","full_name":"Kimmel, Ron","last_name":"Kimmel"}],"date_updated":"2024-11-18T10:05:10Z","intvolume":"      4485","page":"264-275","publisher":"Springer Nature","doi":"10.1007/978-3-540-72823-8_23","publication_status":"published","conference":{"name":"SSVM: Scape Space and Variational Methods in Computer Vision","location":"Ischia, Italy","start_date":"2007-05-30","end_date":"2007-06-02"},"publication_identifier":{"eisbn":["9783540728238"],"isbn":["9783540728221"]},"extern":"1","month":"06","title":"Paretian similarity for partial comparison of non-rigid objects","abstract":[{"text":"In this paper, we address the problem of partial comparison of non-rigid objects. We introduce a new class of set-valued distances, related to the concept of Pareto optimality in economics. Such distances allow to capture intrinsic geometric similarity between parts of non-rigid objects, obtaining semantically meaningful comparison results. The numerical implementation of our method is computationally efficient and is similar to GMDS, a multidimensional scaling-like continuous optimization problem.","lang":"eng"}],"volume":4485,"fulldoi":"https://doi.org/10.1007/978-3-540-72823-8_23","type":"conference"}]