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Human Action Recognition Based on Global Silhouette and Local Optical Flow

机译：基于全球剪影和局部光学流动的人类行动识别

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摘要

Currently, Human Activity Recognition is a research hotspot in the field of machine vision, it involves knowledge of image processing, pattern recognition, artificial intelligence and many other disciplines. Video-based Human Activity Recognition including human area detection, movement and gesture segmentation, objective analysis and behavior understands for activity recognition and so on. In the past, the behavior recognition technology based on the single characteristic was too restrictive, in this paper, we proposed a mixed feature which combined global silhouette feature and local optical flow feature, and this combined representation was used for human action recognition. In the end, test the model with other samples from the database.
机译：目前，人类活动识别是机器视野领域的研究热点，它涉及图像处理，模式识别，人工智能和许多其他学科的知识。基于视频的人类活动识别，包括人类区域检测，运动和手势分割，客观分析和行为对活动识别等等。在过去，基于单个特性的行为识别技术过于限制，本文提出了一种组合全局轮廓特征和局部光学流特征的混合特征，并且这种组合表示用于人类行动识别。最后，使用来自数据库的其他样本测试模型。

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