A fast Binary Biologically Inspired Model for Object Recognition
文献类型：会议论文
| 作者 | Kang Taekoo ; Zhang Huazhen; Lu Yanfeng; Pae Dongsung; Lim Myotaeg
|
| 出版日期 | 2015 |
| 会议日期 | 2015.4.22-4.25 |
| 会议地点 | Seoul, South Korea |
| 关键词 | Hmax Biologically Inspired Model Binary Descriptor Object Recognition |
| 英文摘要 | In this paper, we propose a fast binary based HMAX model (B-HMAX). In our method, we detect corner based interest points after the second layer Cl to extract fewer numbers of features with better distinctiveness, and use binary string to describe the image patches extracted around detected corners, then use hamming distance for matching between two patches in the third layer S2, which is much faster than Euclidean method. Experimental results demonstrate that our proposed B-HMAX model can significantly reduce the total process time, while keeping the accuracy performance as the same with or better than standard HMAX. |
| 语种 | 英语 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/15336]  |
| 专题 | 自动化研究所_复杂系统管理与控制国家重点实验室_机器人应用与理论组 |
| 推荐引用方式 GB/T 7714 | Kang Taekoo,Zhang Huazhen,Lu Yanfeng,et al. A fast Binary Biologically Inspired Model for Object Recognition[C]. 见:. Seoul, South Korea. 2015.4.22-4.25. |
入库方式： OAI收割
来源：自动化研究所
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