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基于语法模型的目标检测Object Detection with Grammar Models |
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| 课程网址: | http://videolectures.net/nips2011_girshick_detection/ |
| 主讲教师: | Ross B. Girshick |
| 开课单位: | 脸书公司 |
| 开课时间: | 2012-09-06 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Compositional models provide an elegant formalism for representing the visual appearance of highly variable objects. While such models are appealing from a theoretical point of view, it has been difficult to demonstrate that they lead to performance advantages on challenging datasets. Here we develop a grammar model for person detection and show that it outperforms previous high-performance systems on the PASCAL benchmark. Our model represents people using a hierarchy of deformable parts, variable structure and an explicit model of occlusion for partially visible objects. To train the model, we introduce a new discriminative framework for learning structured prediction models from weakly-labeled data. |
| 关 键 词: | 图像分析; 计算机科学; 机器学习; 模式识别 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2020-01-13：chenxin |
| 阅读次数: | 59 |