人体行为识别是计算机视觉和模式识别领域的研究热点之一。作为人体行为识别的一个重要分支, 人体异常行为检测近年来也不断得到学界及工业界的重视。人体行为识别研究从早期的依赖人体形状特征发展到基于梯度设计的特征检测, 再到当前随着神经网络的新发展, 深度学习开始广泛应用于行为识别。同时由于红外波段具有适应弱光照环境、可全天候检测等优点, 基于该波段的人体行为识别研究开始兴起, 它也必将成为人体行为识别领域中一个新的研究热点。

Human action recognition is one of the hotspots in the field of computer vision and pattern recognition. As an important branch of human action recognition, abnormal human action detection has arrested attention of academic and business communities constantly. The research on human action recognition has developed from the research based on human shape features to the research based on gradient design. At present, with the new development of neural network, deep learning has been widely used in action recognition. Because infrared wavebands have advantages of dealing with weak light environment and 24-hour monitoring, they have been applied to the research on human action recognition. This will become a new research hotspot in the field of human action recognition.