Please use this identifier to cite or link to this item:
https://doi.org/10.1109/ICIP.2011.6116499
DC Field | Value | |
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dc.title | Pictorial structures for object recognition and part labeling in drawings | |
dc.contributor.author | Sadovnik A. | |
dc.contributor.author | Chen T. | |
dc.date.accessioned | 2018-08-21T04:58:48Z | |
dc.date.available | 2018-08-21T04:58:48Z | |
dc.date.issued | 2011 | |
dc.identifier.citation | Sadovnik A., Chen T. (2011). Pictorial structures for object recognition and part labeling in drawings. Proceedings - International Conference on Image Processing, ICIP : 3613-3616. ScholarBank@NUS Repository. https://doi.org/10.1109/ICIP.2011.6116499 | |
dc.identifier.isbn | 9781457713033 | |
dc.identifier.issn | 15224880 | |
dc.identifier.uri | http://scholarbank.nus.edu.sg/handle/10635/146144 | |
dc.description.abstract | Although the sketch recognition and computer vision communities attempt to solve similar problems in different domains, the sketch recognition community has not utilized many of the advancements made in computer vision algorithms. In this paper we propose using a pictorial structure model for object detection, and modify it to better perform in a drawing setting as opposed to photographs. By using this model we are able to detect a learned object in a general drawing, and correctly label its parts. We show our results on 4 categories. | |
dc.source | Scopus | |
dc.subject | object detection | |
dc.subject | pictorial structures | |
dc.subject | sketch recognition | |
dc.type | Conference Paper | |
dc.contributor.department | OFFICE OF THE PROVOST | |
dc.contributor.department | DEPARTMENT OF COMPUTER SCIENCE | |
dc.description.doi | 10.1109/ICIP.2011.6116499 | |
dc.description.sourcetitle | Proceedings - International Conference on Image Processing, ICIP | |
dc.description.page | 3613-3616 | |
dc.published.state | published | |
Appears in Collections: | Staff Publications |
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