Research On The Statistics Method Of Passenger Flow In The Elevator Based On Kinect

With the development of society, science and technology level continuously improve.The city buildings are more and more intelligent, the use of building function is also more and more diversification. Urban complex appear constantly. In this case, the traffic flow in buildings changes increased, it is impact for elevator dispatch decision in a large building, and it is not conducive to achieve these index of energy saving, fast and comfortable service. This requires a real time data acquisition system of elevator traffic flow, this system can accurately calculate the elevator traffic flow characteristics of the building, and provides data basis for accurate elevator dispatch decision.The accuracy of traffic flow data is the security of elevator traffic pattern recognition system, which provides data support for reasonable elevator dispatch decision. The current, a variety of other elevator traffic flow data collection methods provide inaccurate data except manual collection, so it needs a new elevator traffic flow data collection methods which can provide more accurate data. In this paper, the application of computer vision technology, through the Hough Forests algorithm and depth tracking technology, can effectively calculate elevator traffic flow, and provides a new idea in the area of elevator traffic flow acquisition. The method in this paper has a certain reference value and application prospect.This main work of this paper is as follows:(1)By reviewing the relevant technical documents, the research object of the thesis is confirmed. This paper summarize the development of face detection technology in the area of computer vision technology and future trends, determine the research methods, and based on Hough forests algorithm and depth tracking technology, formulate a scheme of calculating elevator traffic flow.(2)Discuss the application of traffic flow data in various fields, summarize the characteristics of elevator traffic data, this explain that the traffic flow data is time sequence. On the base of reviewing the relevant technical documents, summarize several common methods of traffic flow data statistics.(3)Based on the analysis of the concept of the decision tree and the decision tree generation process, discusses the structure of random forests?the processes of random forest algorithm and advantages-disadvantages. Through the improvement of the random forest binary decision, combines with the Hough transform, confirms a new model of target detection algorithm.(4)Analysis of the actual situation of inside of elevator and passenger in or out of elevator, target is tracked by average depth of target with no feature. This resolves the problem that the target is back to the camera and can not be captured the facial features, and provides a basis for the correct data collection.(5)Using the computer platform and Kinect collect the elevator traffic flow data, makes use of the traffic pattern recognition system to identify elevator traffic pattern, verifies the effectiveness of the algorithm.(6)Summarize the study of this paper, and make a prospect to the next research.