Smart Digital Signage:Audience Expression Analysis
20131231 - 20150629
Dr Chen-jung Tsai
A. Human expression recognition and analysis algorithm development (1) Static human Face expression recognition and analysis (a) 6 fundamental human expressions recognition for still image: Happiness, Sadness, Fear, Anger, Disgust and Surprise (b) > 80% accuracy (2) Dynamic human Face expression/emotion Analysis (a) Human emotion analysis for video sequence (b) > 80% accuracy B. Smart Digital Signage (1) Thin high-brightness LED backlight for digital signage (a) LED light-bar with 2nd optical lens for high-brightness backlight (>1500nit) with 40% light mixing distance reduction (b) Brightness: ≥1500 nits Tiled (2*2) LCD Size: ≥100”. (c) High resolution ambient adaptive power management (Power saving >50%) (2) 3D gesture recognition algorithm development for digital signage (a) Detection distance: 1 - 3 m (b) Detection functions: track and recognize a single user: gestures including clicking, dragging, sliding, rotating, enlarging and shrinking 3D objects (3) User ID verification by face recognition for digital signage (a) < 2% false accept rate; <3% false reject rate (b) Fixed acquisition/testing condition (angle, illumination, expression and decoration) C. Integrated Audience Analysis System (1) Low-cost Intelligent Audience Analysis (IAA) (a) People counting and watch time recording (b) > 90% accuracy (2) High performance version (a) > 90% accuracy in people counting and watch time recording (b) > 80% accuracy in expression, age and gender classification (c) Near-frontal-view face (left-right:30 degree). (d) Detection Distance: Face Detection and Tracking: 0.3~6m, Age , Gender and expression:1~3m.
Dr Enboa WU Ms Ying, Anna LIU Mr Kin Lung, Kenny CHAN Dr Xiu Ling ZHU Dr Zhao, Fiona Wang Mr Chang-Li WU Dr Chi Yong Mr Yuk lung, Alex Cheung Mr Wei-Ping Tang Ms Wei, Wendy Zhang Dr Yan Wang Mr Derek Dehua Liu Dr Xueyan TANG Mr Chun Yip Wong Mr Chan Kwok Chung Mr Dennis Chi Kin Wong Mr Wai Kin Luk Mr Pei Chin Ryan Chung Mr Weiwen, Wilman Zou Mr Hui Hu Mr Haocheng Han Dr Mi Suen Lee Ms Jie, Fiona Lu Dr Jie Kou Mr Guanghua Huang
Chinese Academy of Science (CAS) HK Ronglee Technology Limited HK Ronglee Technology Limited (Technology Licensing) [Sponsor] Shenzhen Suijing Optoelectronics Technology Co., Ltd. [Sponsor] The University of Nottingham Wintronic Technology Limited Wuhu Retop Electronics Co., Ltd. [Sponsor]
Marketing surveys have revealed that the digital advertising is developing at a rapid pace. Today, huge amount of advertisements are still employing the traditional one-way approach in which information are transmitted to the audience without acquiring their feedbacks or carrying out any interactions. Smart digital signage will certainly enter into a new development stage if it can be customized: delivering the information which is of interest to the audience. Today's market lacks such products which are mature enough for mass commercialization. This project aims to develop the technologies for next generation smart digital signage. In order to achieve the goal, this project will focus on the development of the following technologies included (1) Audience expression analysis: to determine whether further information will be forwarded to the user if he/she finds the current information interesting; (2) Smart digital signage, including: high-brightness LED backlight for sun-readability; non-touch gesture control system to enable users to manipulate the displayed information via both touch and non-touch methods; and human face recognition for user log-in; (3) Integrated / embedded audience analysis system: to collect, analyze and deliver statistical details such as user’s expression, attention level, age and gender.