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July 5, 2019 05:20 pm

How AI Helped Improve Crowd Counting in Hong Kong Protests

K.K. Rebecca Lai, Jin Wu and Lingdong Huang, writing for the Times: Crowd estimates for Hong Kong's large pro-democracy protests have been a point of contention for years. The organizers and the police often release vastly divergent estimates. This year's annual pro-democracy protest on Monday, July 1, was no different. Organizers announced 550,000 people attended; the police said 190,000 people were there at the peak. But for the first time in the march's history, a group of researchers combined artificial intelligence and manual counting techniques to estimate the size of the crowd [Editor's note: the link may be paywalled], concluding that 265,000 people marched. The high density of the crowd and the moving nature of these protests make estimating the turnout very challenging. For more than a decade, groups have stationed teams along the route and manually counted the rate of people passing through to derive the total number of participants. Though the use of A.I. does not make the calculation definitive, the technology helps produce a more precise estimate because it uses computers to try to count every person. Since 2003, Paul Yip, a social sciences professor at Hong Kong University, has been producing a count of the size of protests held annually on July 1, the anniversary of Hong Kong's 1997 handover from Britain to China. With the hopes of creating a more robust estimate this year, Mr. Yip teamed up with Edwin Chow from Texas State University and Raymond Wong from C&R Wise AI, a local technology company, to use artificial intelligence to count the crowd at the march. Using open source software, The New York Times developed a computer model to illustrate how artificial intelligence could be used to recognize people and objects moving within a video. Analyzing a short video clip recorded on Monday, The Times's model tried to detect people based on color and shape, and then tracked the figures as they moved across the screen. This method helps avoid double counting because the crowd generally flowed in one direction.

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