Representing shape with a spatial pyramid kernel Export

@inproceedings{bosch07, abstract = {The objective of this paper is classifying images by the object categories they contain, for example motorbikes or dolphins. There are three areas of novelty. First, we introduce a descriptor that represents local image shape and its spatial layout, together with a spatial pyramid kernel. These are designed so that the shape correspondence between two images can be measured by the distance between their descriptors using the kernel. Second, we generalize the spatial pyramid kernel, and learn its level weighting parameters (on a validation set). This significantly improves classification performance. Third, we show that shape and appearance kernels may be combined (again by learning parameters on a validation set).}, address = {New York, NY, USA}, author = {Bosch, Anna and Zisserman, Andrew and Munoz, Xavier}, booktitle = {Proceedings of ACM International Conference on Image and Video Retrieval}, citeulike-article-id = {1701946}, citeulike-linkout-0 = {http://portal.acm.org/citation.cfm?id=1282340}, citeulike-linkout-1 = {http://dx.doi.org/10.1145/1282280.1282340}, doi = {10.1145/1282280.1282340}, isbn = {978-1-59593-733-9}, journal = {Proceedings of ACM International Conference on Image and Video Retrieval}, keywords = {bosch07}, location = {Amsterdam, The Netherlands}, pages = {401--408}, posted-at = {2008-11-17 03:04:42}, priority = {2}, publisher = {ACM}, title = {Representing shape with a spatial pyramid kernel}, url = {http://dx.doi.org/10.1145/1282280.1282340}, year = {2007} }

TY - CONF ID - bosch07 L3 - citeulike-article-id:1701946 N2 - The objective of this paper is classifying images by the object categories they contain, for example motorbikes or dolphins. There are three areas of novelty. First, we introduce a descriptor that represents local image shape and its spatial layout, together with a spatial pyramid kernel. These are designed so that the shape correspondence between two images can be measured by the distance between their descriptors using the kernel. Second, we generalize the spatial pyramid kernel, and learn its level weighting parameters (on a validation set). This significantly improves classification performance. Third, we show that shape and appearance kernels may be combined (again by learning parameters on a validation set). CY - Amsterdam, The Netherlands JF - Proceedings of ACM International Conference on Image and Video Retrieval SN - 978-1-59593-733-9 AD - New York, NY, USA EP - 408 TI - Representing shape with a spatial pyramid kernel PB - ACM T2 - Proceedings of ACM International Conference on Image and Video Retrieval SP - 401 KW - bosch07 AU - Bosch, Anna AU - Zisserman, Andrew AU - Munoz, Xavier PY - 2007/// UR - http://dx.doi.org/10.1145/1282280.1282340 ER -