Study on human behavior recognition based on VLAD and CNN

• 1、Harbin Engineering University College of information and Communication Engineering,Harbin,150001

Abstract：Human behavior recognition is the key technology in many applications, such as video surveillance, human-computer interaction, virtual reality and video retrieval, so human behavior recognition technology intelligent has a very high research value and application prospect, especially in today\'s video data explosive growth period. Deep learning is a research field at this stage is very hot, especially the CNN model has achieved great success in image recognition, artificial features compared with traditional method, CNN feature has an absolute advantage in the expression characteristics of the original data, has been gradually replaced by HOG and SIFT as artificial feature the mainstream feature extraction method. VLAD is a video feature data of different sizes into the same size feature vector, through the VLAD feature representation can make the video data meet the general classifier requirements and classification. This paper presents human behavior recognition method based on VLAD feature extraction a CNN feature, and verified in the Youtube database, finally achieved a higher recognition accuracy, and prove that CNN combined with VLAD is a very effective method for human behavior recognition.

Keywords： human behavior recognition deep learning CNN VLAD feature extraction feature representation