Real-Time Top-View People Counting Based on a Kinect and NVIDIA Jetson TK1 Integrated Platform

• Published in: 2016 IEEE 16th International Conference on Data Mining Workshops (ICDMW) pp. 468 - 473
• Main Authors: Guangqin Li, Peng Ren, Xinrong Lyu, He Zhang
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.12.2016
• Subjects: Cameras; Graphics processing units; Head; Image resolution; Jetson TK1; Kinect; People counting; Real-time systems; Signal processing algorithms; Top-view; Universal Serial Bus; Waterfilling
• ISSN: 2375-9259
• DOI: 10.1109/ICDMW.2016.0073

In this paper, we describe how to establish an embedded framework for real-time top-view people counting. The development of our system consists of two parts, i.e. establishing an embedded signal processing platform and designing a people counting algorithm for the embedded system. For the hardware platform construction, we use Kinect as the camera and exploit NVIDIA Jetson TK1 board as the embedded processing platform. We describe how to build a channel to make Kinect for windows version 2.0 communicate with Jetson TK1. Based on the embedded system, we adapt a water filling based scheme for top-view people counting, which integrates head detection based on water drop, people tracking and counting. Gaussian Mixture Model is used to construct and update the background model. The moving people in each video frame are extracted using background subtraction method. Additionally, the water filling algorithm is used to segment head area as Region Of Interest(ROI). Tracking and counting people are performed by calculating the distance of ROI center point before and after the frame. The whole framework is flexible and practical for real-time application.