Robust Feature Encoding with Neighborhood Information for Image Classification
文献类型：会议论文
| 作者 | Bingyuan Liu; Jing Liu ; Chunjie Zhang; Maolin Chen; Hanqing Lu
|
| 出版日期 | 2013 |
| 会议日期 | July 26-28, 2013 |
| 会议地点 | Qingdao, China |
| 关键词 | Image Classification Feature Encoding |
| 英文摘要 | The bag of visual words (BoW) model is one of the most successful model in image classification task. However, the major problem of the BoW model lies in the determination of visual words, which consists of codebook training and feature encoding phases. The traditional K-means and hard-assignment method completely ignore the structure of the local feature space, leading to high loss of information. To alleviate the information loss, we propose to incorporate the neighborhood information of the features into the codebook training and feature encoding process. We firstly propose a model to roughly measure the influence of the distribution of the neighboring features. Then we combine the proposed model with the traditional K-means method in a probability perspective to train the visual codebook. Finally, in the feature encoding phase, both the hard-assignment and soft-assignment method are improved with the proposed neighborhood information term. We investigate our method on two popular datasets: 15-Scenes and Caltech-101. Experimental results demonstrate the effectiveness of our proposed method. |
| 会议录 | Proceedings of the Seventh International Conference on Image and Graphics
 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/13445]  |
| 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 |
| 通讯作者 | Jing Liu |
| 推荐引用方式 GB/T 7714 | Bingyuan Liu,Jing Liu,Chunjie Zhang,et al. Robust Feature Encoding with Neighborhood Information for Image Classification[C]. 见:. Qingdao, China. July 26-28, 2013. |
入库方式： OAI收割
来源：自动化研究所
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