图 书 馆
使用局部特征之间的成对统计学对食物识别Food Recognition Using Statistics of Pairwise Local Features |
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| 课程网址: | http://videolectures.net/cvpr2010_yang_frus/ |
| 主讲教师: | Shulin (Lynn) Yang |
| 开课单位: | 华盛顿大学 |
| 开课时间: | 2010-07-19 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Food recognition is difficult because food items are deformable objects that exhibit significant variations in appearance. We believe the key to recognizing food is to exploit the spatial relationships between different ingredients (such as meat and bread in a sandwich). We propose a new representation for food items that calculates pairwise statistics between local features computed over a soft pixellevel segmentation of the image into eight ingredient types. We accumulate these statistics in a multi-dimensional histogram, which is then used as a feature vector for a discriminative classifier. Our experiments show that the proposed representation is significantly more accurate at identifying food than existing methods. |
| 关 键 词: | 食物; 分割计算; 多维直方图 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-03-13：lxf |
| 阅读次数: | 88 |