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视觉检测及其应用Validating the Detection of Everyday Concepts in Visual Lifelogs |
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| 课程网址: | http://videolectures.net/samt08_doherty_vdec/ |
| 主讲教师: | Aiden Roger Doherty |
| 开课单位: | 都柏林城市大学 |
| 开课时间: | 2008-12-18 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | The Microsoft SenseCam is a small lightweight wearable camera used to passively capture photos and other sensor readings from a user's day-to-day activities. It can capture up to 3,000 images per day, equating to almost 1 million images per year. It is used to aid memory by creating a personal multimedia lifelog, or visual recording of the wearer's life. However the sheer volume of image data captured within a visual lifelog creates a number of challenges, particularly for locating relevant content. Within this work, we explore the applicability of semantic concept detection, a method often used within video retrieval, on the novel domain of visual lifelogs. A concept detector models the correspondence between low-level visual features and high-level semantic concepts (such as indoors, outdoors, people, buildings, etc.) using supervised machine learning. By doing so it determines the probability of a concept's presence. We apply detection of 27 everyday semantic concepts on a lifelog collection composed of 257,518 SenseCam images from 5 users. The results were then evaluated on a subset of 95,907 images, to determine the precision for detection of each semantic concept and to draw some interesting inferences on the lifestyles of those 5 users. We additionally present future applications of concept detection within the domain of lifelogging. |
| 关 键 词: | 可穿戴式相机; 视觉记录; 视觉记忆; 视觉生命线; 视频检索; 感念检测; 未来应用 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2020-06-08：cxin |
| 阅读次数: | 29 |