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<titleInfo><title>Learning to localize objects with structured output regression</title></titleInfo>

  
  
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  <title>LNCS</title>
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<name type="personal">
  <namePart type="given">Matthew</namePart>
  <namePart type="family">Blaschko</namePart>
  <role><roleTerm type="text">author</roleTerm> </role></name>
<name type="personal">
  <namePart type="given">Christoph</namePart>
  <namePart type="family">Lampert</namePart>
  <role><roleTerm type="text">author</roleTerm> </role><identifier type="local">40C20FD2-F248-11E8-B48F-1D18A9856A87</identifier><description xsi:type="identifierDefinition" type="orcid">0000-0001-8622-7887</description></name>









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  <namePart>ECCV: European Conference on Computer Vision</namePart>
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<abstract lang="eng">Sliding window classifiers are among the most successful and widely applied techniques for object localization. However, training is typically done in a way that is not specific to the localization task. First a binary classifier is trained using a sample of positive and negative examples, and this classifier is subsequently applied to multiple regions within test images. We propose instead to treat object localization in a principled way by posing it as a problem of predicting structured data: we model the problem not as binary classification, but as the prediction of the bounding box of objects located in images. The use of a joint-kernel framework allows us to formulate the training procedure as a generalization of an SVM, which can be solved efficiently. We further improve computational efficiency by using a branch-and-bound strategy for localization during both training and testing. Experimental evaluation on the PASCAL VOC and TU Darmstadt datasets show that the structured training procedure improves pe rformance over binary training as well as the best previously published scores.</abstract>

<originInfo><publisher>Springer Nature</publisher><dateIssued encoding="w3cdtf">2008</dateIssued><place><placeTerm type="text">Marseille, France</placeTerm></place>
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<language><languageTerm authority="iso639-2b" type="code">eng</languageTerm>
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<relatedItem type="host"><titleInfo><title>10th European Conference on Computer Vision</title></titleInfo>
  <identifier type="isbn">9783540886815</identifier><identifier type="doi">10.1007/978-3-540-88682-2_2</identifier>
<part><detail type="volume"><number>5302</number></detail><extent unit="pages">2 - 15</extent>
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<chicago>Blaschko, Matthew, and Christoph Lampert. “Learning to Localize Objects with Structured Output Regression.” In &lt;i&gt;10th European Conference on Computer Vision&lt;/i&gt;, 5302:2–15. Springer Nature, 2008. &lt;a href=&quot;https://doi.org/10.1007/978-3-540-88682-2_2&quot;&gt;https://doi.org/10.1007/978-3-540-88682-2_2&lt;/a&gt;.</chicago>
<mla>Blaschko, Matthew, and Christoph Lampert. “Learning to Localize Objects with Structured Output Regression.” &lt;i&gt;10th European Conference on Computer Vision&lt;/i&gt;, vol. 5302, Springer Nature, 2008, pp. 2–15, doi:&lt;a href=&quot;https://doi.org/10.1007/978-3-540-88682-2_2&quot;&gt;10.1007/978-3-540-88682-2_2&lt;/a&gt;.</mla>
<ama>Blaschko M, Lampert C. Learning to localize objects with structured output regression. In: &lt;i&gt;10th European Conference on Computer Vision&lt;/i&gt;. Vol 5302. Springer Nature; 2008:2-15. doi:&lt;a href=&quot;https://doi.org/10.1007/978-3-540-88682-2_2&quot;&gt;10.1007/978-3-540-88682-2_2&lt;/a&gt;</ama>
<apa>Blaschko, M., &amp;#38; Lampert, C. (2008). Learning to localize objects with structured output regression. In &lt;i&gt;10th European Conference on Computer Vision&lt;/i&gt; (Vol. 5302, pp. 2–15). Marseille, France: Springer Nature. &lt;a href=&quot;https://doi.org/10.1007/978-3-540-88682-2_2&quot;&gt;https://doi.org/10.1007/978-3-540-88682-2_2&lt;/a&gt;</apa>
<ieee>M. Blaschko and C. Lampert, “Learning to localize objects with structured output regression,” in &lt;i&gt;10th European Conference on Computer Vision&lt;/i&gt;, Marseille, France, 2008, vol. 5302, pp. 2–15.</ieee>
<ista>Blaschko M, Lampert C. 2008. Learning to localize objects with structured output regression. 10th European Conference on Computer Vision. ECCV: European Conference on Computer Vision, LNCS, vol. 5302, 2–15.</ista>
<short>M. Blaschko, C. Lampert, in:, 10th European Conference on Computer Vision, Springer Nature, 2008, pp. 2–15.</short>
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