Beyond spatial pyramids: A new feature extraction framework with dense spatial sampling for image classification
文献类型：会议论文
| 作者 | Yan, Shengye ; Xu, Xinxing ; Xu, Dong ; Lin, Stephen ; Li, Xuelong |
| 出版日期 | 2012 |
| 会议名称 | 12th european conference on computer vision, eccv 2012 |
| 会议日期 | ctober 7, 2012 - october 13, 2012 |
| 会议地点 | florence, italy |
| 页码 | 473-487 |
| 英文摘要 | we introduce a new framework for image classification that extends beyond the window sampling of fixed spatial pyramids to include a comprehensive set of windows densely sampled over location, size and aspect ratio. to effectively deal with this large set of windows, we derive a concise high-level image feature using a two-level extraction method. at the first level, window-based features are computed from local descriptors (e.g., sift, spatial hog, lbp) in a process similar to standard feature extractors. then at the second level, the new image feature is determined from the window-based features in a manner analogous to the first level. this higher level of abstraction offers both efficient handling of dense samples and reduced sensitivity to misalignment. more importantly, our simple yet effective framework can readily accommodate a large number of existing pooling/coding methods, allowing them to extract features beyond the spatial pyramid representation. to effectively fuse the second level feature with a standard first level image feature for classification, we additionally propose a new learning algorithm, called generalized adaptive ℓp -norm multiple kernel learning (ga-mkl), to learn an adapted robust classifier based on multiple base kernels constructed from image features and multiple sets of pre-learned classifiers of all the classes. extensive evaluation on the object recognition (caltech256) and scene recognition (15scenes) benchmark datasets demonstrates that the proposed method outperforms state-of-the-art image classification algorithms under a broad range of settings. |
| 收录类别 | EI |
| 产权排序 | 3 |
| 会议主办者 | google; national robotics engineering center (nrec); adobe; microsoft research; mitsubishi electric |
| 会议录 | computer vision, eccv 2012 - 12th european conference on computer vision, proceedings
 |
| 会议录出版者 | springer verlag, tiergartenstrasse 17, heidelberg, d-69121, germany |
| 会议录出版地 | germany |
| 语种 | 英语 |
| ISSN号 | 3029743 |
| ISBN号 | 9783642337642 |
| 源URL | [http://ir.opt.ac.cn/handle/181661/20539]  |
| 专题 | 西安光学精密机械研究所_光学影像学习与分析中心 |
| 推荐引用方式 GB/T 7714 | Yan, Shengye,Xu, Xinxing,Xu, Dong,et al. Beyond spatial pyramids: A new feature extraction framework with dense spatial sampling for image classification[C]. 见:12th european conference on computer vision, eccv 2012. florence, italy. ctober 7, 2012 - october 13, 2012. |
入库方式： OAI收割
来源：西安光学精密机械研究所
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