Tokyo, October 24, 2016 - NEC Corporation (NEC; TSE: 6701) today announced the strengthening of its crowd behavior analysis technology (*1), enabling it to accurately estimate and predict the degree of congestion of a large crowd and the flow of people in real-time by utilizing specialized security camera systems.

This newly developed technology, belonging to the cutting-edge portfolio of NEC the WISE (*2) artificial intelligence (AI) technologies, analyzes security camera footage to create data that accurately defines the degree of congestion and the flow of people in environments (*3) consisting of tens of thousands of people, including large facilities or event venues. Moreover, it employs NEC's proprietary crowd model to simulate the behavior of people in a crowded environment, such how individuals follow or avoid collision with each other, to optimize analysis and accurately estimate or predict various situations in real-time.

"This technology predicted the degree of congestion in areas of a large-scale sporting event 10 minutes in advance within a 20% margin of error. This enables the real-time guidance of crowds, which helps to prevent over congestion and enhance safety," said Akio Yamada, General Manager, Data Science Research Laboratories, NEC Corporation.

Key features of this technology include the following:

1. Quantitatively understanding the degree of congestion and the flow of people, even in a crowded environment, by analyzing security camera footage
   By combining technology to visualize crowd conditions from security footage (the degree of congestion and estimated number of people) with technology to extract the movement in this footage, NEC has developed a new technology to estimate multiple elements of a crowd's movement, thereby enabling the quantitative understanding of the number of people moving in each direction.
   
   This technology makes it possible to accurately estimate the degree of congestion and the distribution of a crowd's flow within the field of view of a camera by integrating and analyzing the movements of a crowd. As a result, it is possible to understand the number of people passing through an area in each direction, even in a very crowded environment where people appear to be overlapping each other.


2. Predicting crowd conditions several minutes to tens of minutes in advance based on information about the degree of congestion and the flow of people obtained from several locations
   NEC developed a crowd model to accurately estimate and predict the flow of people in real-time by incorporating information on the density and flow of a crowd for analysis.
   
   The crowd model expresses the behavior of people in a crowded environment and displays the movements of each agent, such as individuals moving to avoid collisions, and traveling through empty spaces, in order to accurately simulate crowd conditions.

NEC will exhibit these technologies at the C&C User Forum & iEXPO 2016 at the Tokyo International Forum from Tuesday, November 1 to Wednesday, November 2, 2016. For more information, please visit: https://uf-iexpo.nec/

NEC will make presentations about these technologies at the ViEW2016: Vision Engineering Workshop 2016 at Pacifico Yokohama on Thursday, December 8 and Friday, December 9.
http://www.tc-iaip.org/view2016/

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Notes:

• *1 November 7, 2013: NEC technology detects changes in crowd behavior and promotes security
  http://www.nec.com/en/press/201311/global_20131107_02.html
• *2 July 19, 2016: NEC announces new AI technology brand, "NEC the WISE"
  http://www.nec.com/en/press/201607/global_20160719_01.html
  
  NEC's AI (Artificial Intelligence) Research
  http://www.nec.com/en/global/rd/crl/ai/index.html
• *3 Crowded environment: An environment which exceeds two people/m2 for walking space, and four people/m2 while stationary

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