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Discriminative human action recognition using HOI descriptor and key poses

机译:使用HOI描述符和关键姿势进行区分性人类动作识别

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Action recognition on large categories of unconstrained videos is still a challenging one due to appearance variations, recording settings and inter-personal differences. A highly discriminating descriptor is introduced which afford context information to recognition human actions in a video. We focus to discriminate the actions having identical spatio-temporal relations by human-object interaction analysis and with similar motion pattern by pose estimation. Robust solutions obtained in this process find immense applications in domains such as visual surveillance, video retrieval and human-computer interaction. We validate our approach on two human activity datasets and show performance improvements over competing state-of-the-art representations.
机译:由于外观变化,录制设置和人际差异,在大范围不受约束的视频上进行动作识别仍然是一个挑战。引入了高度区分的描述符,该描述符提供上下文信息以识别视频中的人类动作。我们专注于通过人-物体交互分析来区分具有相同时空关系的动作,并通过姿势估计来区分具有相似运动模式的动作。在此过程中获得的强大解决方案在视觉监控,视频检索和人机交互等领域中找到了巨大的应用。我们在两个人类活动数据集上验证了我们的方法,并显示了与竞争的最先进表示相比性能的提高。

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