Boosting part-sense multi-feature learners toward effective object detection
文献类型：期刊论文
| 作者 | Chen, Shi; Wang, Jinqiao ; Ouyang, Yi; Wang, Bo; Xu, Changsheng; Lu, Hanqing
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| 刊名 | COMPUTER VISION AND IMAGE UNDERSTANDING
 |
| 出版日期 | 2011-03-01 |
| 卷号 | 115期号:3页码:364-374 |
| 关键词 | AdaBoost Object detection Multi-feature learners L(1)-regularized gradient boosting |
| 英文摘要 | AdaBoost has been applied to object detection to construct the detectors with high performance of discrimination and generalization by single-feature learner. However, the poor discriminative power of extremely weak single-feature learners limits its application for general object detection. In this paper, we propose a novel comprehensive learner design mechanism toward effective object detection in terms of both discrimination and generalization abilities. Firstly, the part-sense multi-feature learners are designed to linearly combine the multiple local features to improve the descriptive and discriminative capacity of the learner. Secondly, we formulate the feature selection in part-sense multi-feature learner as a weighted LASSO regression. Using Least Angle Regression (LARS) method, our approach can choose features adaptively, efficiently and as few as possible to guarantee generalization performance. Finally, a robust L1-regularized gradient boosting is proposed to integrate our part-sense sparse features learner into an object classifier. Extensive experiments and comparisons on the face dataset and the human dataset show the proposed approach outperforms the traditional single-feature learner and other multi-feature learners in discriminative and generalization abilities. (C) 2010 Elsevier Inc. All rights reserved. |
| WOS标题词 | Science & Technology ; Technology |
| 类目[WOS] | Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic |
| 研究领域[WOS] | Computer Science ; Engineering |
| 关键词[WOS] | FACE DETECTION ; ALGORITHMS |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000287772400008 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/3326]  |
| 专题 | 自动化研究所_模式识别国家重点实验室_图像与视频分析团队 |
| 作者单位 | Chinese Acad Sci, Inst Automat, Beijing, Peoples R China |
| 推荐引用方式 GB/T 7714 | Chen, Shi,Wang, Jinqiao,Ouyang, Yi,et al. Boosting part-sense multi-feature learners toward effective object detection[J]. COMPUTER VISION AND IMAGE UNDERSTANDING,2011,115(3):364-374. |
| APA | Chen, Shi,Wang, Jinqiao,Ouyang, Yi,Wang, Bo,Xu, Changsheng,&Lu, Hanqing.(2011).Boosting part-sense multi-feature learners toward effective object detection.COMPUTER VISION AND IMAGE UNDERSTANDING,115(3),364-374. |
| MLA | Chen, Shi,et al."Boosting part-sense multi-feature learners toward effective object detection".COMPUTER VISION AND IMAGE UNDERSTANDING 115.3(2011):364-374. |
入库方式： OAI收割
来源：自动化研究所
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