Behavior Recognition System Based on Convolutional Neural Network

Our this article is on this research paper . 
Credit : Bo YU

What we will do ?

We build a set of human behavior recognition system based on the convolution neural network constructed for the specific human behavior in public places. 

(i) : Firstly, video of human behavior data set will be segmented into images, then we process the images by the method of background subtraction to extract moving foreground characters of body. (ii). Secondly, the training data sets are trained into the designed convolution neural network, and the depth learning network is constructed by stochastic gradient descent.

(iii). Finally, the various behaviors of samples are classified and identified with the obtained network model, and the recognition results are compared with the current mainstream methods. The result show that the convolution neural network can study human behavior model automatically and identify human’s behaviors without any manually annotated trainings. 

Human behavior recognition is mainly divided into two processes: the identification and understanding of human behavior feature extraction and motion .

This algorithm is mainly composed of three parts, 

1.  Video pretreatment, 2. Model training 3. Behavior recognition part. 

In the video preprocessing part, firstly the original behavior of video preprocessing, using block updating background subtraction method to achieve target detection, two value image motion information is extracted, then the image input channel convolutional neural network, through the iterative training parameters of the network, to construct a model for convolution Behavior Recognition . Finally, you can use this network to identify human behavior .

Implementation Code on Github : Code