Students: Anurag Anjaria, Charles Hansen, Jin Bai, Mai KanchanabalProfessors: Dr. Edward J. Delp, Dr. Yung-Hsiang Lu

CAM2Continuous Analysis of Many CAMeras

The ProblemCurrently there is no common computing infrastructure which can support continuous analysis of many internet connected cameras and so researchers are unable to harness this vast amount of data for analysis.

The Infrastructure1. A large number of publicly available cameras and their properties2. A set of functions common to different analysis programs and an API for developing

the analysis programs3. A resource manager (system) which optimizes the resources needed for running the

analysis programs

Possible ApplicationsUses of the system include:• Traffic analysis to improve congestion or detect accidents• Weather observation to increase the accuracy of existing weather models• Population detection and areas of high

User Interface TeamPurpose: Further develop the CAM2 web applicationProgress:• Live stream data from server to application• Display of all IP streams for test cameras• Menu displaying grid of camera tiles

Cloud-Based Distributed System ArchitectureAbove is a lower level view of the interactions of the distributed system from application upload to the job scheduler. Two monitors provide information about the performance of the system and the data flow during operation. A database holds everything from logins for the website to reports generated automatically by the manager.

Image Processing TeamPurpose: Developing software applications in Python to perform image analysisProgress:• Heat map generation on video stream • Optimization of analysis on video over time• Population counting of people in video over time• Region of interest selection for more detailed analysis

Future DevelopmentShort Term:• Continue improvements on web application• Bring total camera count up to one-hundred thousand• Continue optimizations on heat map generation and

detection

Long Term:• Scale up to millions of cameras and thousands of workers• Population graphing in real time• Automated testing• Large scale implementation of detection and analysis

Heat Map GenerationThe algorithm compares the values of a video’s pixels over time, creating hot-spots depending on how often the pixel’s value changes. The hotspots are overlaid on top of an image, creating a heat map.

Data Integrity and TestingPurpose: develop testing infrastructure and explore video transmission technologiesProgress:• Implementation of static server using NGINX for data storage• Serve archived videos and images from server• Optimized RAID configurations• Transmission speed experiments and optimizations

Camera TeamPurpose: Understand and integrate existing camera infrastructure within CAM2 Progress:• Thousands of cameras added to database• Capture of JavaScript-generated URLs• Updates to database of cameras

People DetectionThis algorithm utilizes the method of Histogram of Oriented Gradients (HOG) which combined with a Support Vector Machine (SVM) and OpenCV allows for detection of multiple people in an image or video

Sample Heat Map People Detection