What are the top 10 face recognition companies? What are the face recognition technology companies in China? A list of face recognition algorithm rankings. When it comes to biometrics, the most closely linked with life is fingerprint recognition and face recognition. The brush face payment function and the application of some face detection authentication functions have made us more and more exposed to the new face recognition technology. This article mainly introduces some companies with face recognition technology and their latest algorithm rankings. 1. Cloud From Technology Backed by the "father of computer vision", the Chinese Academy of Sciences' laboratory entrepreneurship team founded Technology In addition to the alumni from China National University of Science and Technology, the team members of the cloud science and technology team also come from top institutes of the Chinese Academy of Sciences, UIUC, IBM, NEC, MicroSoft, and other top universities and research institutions in the world; As of November 2016, one and a half years after its establishment, the R&D team has expanded to more than 200 people, making it the nation's largest face recognition R&D team; In addition, commercial exploration began in the fields of finance, security, and education. The IBIS platform made it the largest supplier in the banking industry. The application of the dynamic face recognition system in Guangdong became a benchmark and was promoted throughout the country; The president of the Chinese Academy of Sciences visited the team once every year during the Chinese Academy of Sciences and paid great attention to it. When meeting with foreign leaders and delegations, they only took the cloud from the two companies of Science and Technology and HKUST to represent China Zhizhi. The first brush face payment prototype system. The first commercial face recognition remote opening system. It stands out among all the computer vision teams within the Chinese Academy of Sciences, and is exclusively responsible for strategic pilot technology Class A special projects. The only R&D enterprise that participates in the formulation of national standards, standards and standards for face recognition. The only company that allows one of the four major banks to use face recognition across the country. According to the actual needs of the 2B industry, it has created a full industry chain model and a rapid deployment platform. In the POC test, it greatly advanced the face recognition manufacturers from Japan and Germany. API Service Technology Platform Recruitment 2. Emotient Emotient Receives $6 Million B Round Investment (2014/03/10) Emotient originated from the Machine Perception Lab at the University of California. Their ultimate goal is to create an "ubiquitous" human emotion analysis system. Analysis of expressions does not require special hardware devices, and full-face images from at least 48 pixels from ear to ear can be satisfied. Emotient also provides an API interface that can easily integrate its technology with any hardware or software. Currently, Emotient has partnered with Google Glass to begin private testing. Emotient will also be used as part of the Intel RealSense Technology SDK to quickly connect with developers around the world. Emotient has deployed its facial expression recognition service to the retail industry to help retailers increase sales through real-time analysis of customer perception. Emotient uses artificial intelligence to scan people's faces, and then in a few seconds to interpret the meaning represented by their facial expressions. This technology used to help advertisers and salespeople to judge consumers' reactions to advertisements or products. 3, Founded in 2009, Affectiva is a cloud-based facial emotion recognition and analysis service company that uses Facial Coding to capture facial movements of identified objects such as frowning, raising eyebrows, giggling, smiling, etc. to determine people's emotions. It is also mainly used for marketing, but Affectiva will launch its SDK development tools for third-party developers next month. Egyptian scientist Ranael Kaliouby. She currently lives in Boston and founded the company Affectiva in 2009. Many employees are from MIT Affectiva is located in Waltham, Mass., in the office park behind the two-way street business district and is part of the corridor that Boston established to imitate Silicon Valley. The iPad with Affdex was reduced to a “classifier†that tracks four emotions: happy, confused, surprised and bored. Use this software to scan the face to identify emotions; if there are multiple faces at the same time, it will separate them, one by one. Then, identifying the main parts of the face - the mouth, nose, eyes and eyebrows - position the pixel points to each part, and then use a simple geometric model to render the feature. Ffedex has always been used as a reliable emotional speculation tool - a tool that can enter the subconscious domain. Affdex has done 80,000 frowns. When she stood on stage and announced the results, she said: "Our accuracy rate can reach 90%." Her company has analyzed more than 2 million videos, and the participants came from more than 80 countries around the world. When Affectiva was founded, she had trained her software with hundreds of expressions. Affectiva depends on the research of Paul Ekman. He is a psychology researcher who started researching and establishing authoritative theoretical systems at the age of sixty-six: Humans have at least six universal facial expressions. These facial expressions, regardless of gender, age, or cultural background, will be in everyone’s The face is exactly the same. Ekman is committed to deciphering these emotions. He breaks them down into 46 independent actions, calling them a combination of "action units." Dividing them into deformable and non-deformable points, and using these non-deformable points as anchor points can help us determine the distance that other points move. Facial recognition analysis service Affectiva will push the SDK package, hoping to play a role in areas other than marketing such as games, teaching, etc. Affectiva's research found that people's reactions to advertising - expression data can be used to predict sales volume, with an accuracy of 75%, although this is only a 5% improvement over traditional market research methods. Affectiva has collected more than 1 billion facial expressions all over the world Previously it had obtained a total investment of US$20 million (Li Ka-shing participated in its investment) and employed 35 employees. (13 years data) McCann (Affectiva in Barcelona) The McCann Division did not help the club develop an advertising campaign plan. Instead, it recommended that it install an Affdex-like software on the seat and promised to open the audience theater free of charge. However, for each laugh, it costs 0.3 Euro and the limit is 80. . If the audience tries to cover their smiles or hide their laughs, they will be charged full price: 24 Euros. The turnover of this shop suddenly came up. The theaters of the United States, France and South Africa all contacted McCann in hopes of knowing more ways. 4ã€Face++ Tsinghua Venture Team Launches Face Cloud Recognition Open Platform Face++ Apart from several Tsinghua alumni, the Face++ team members also have research and development personnel from Columbia University, Oxford University in the United Kingdom, and the University of Southern California in the United States. In the financial, security, and retail sectors, they began to explore the successful development of Face++Financial, Face++Security, Face++BI and other vertical face verification solution products. Magic Man Camera is the world's first mobile application that turns real people into humorous comics. With more than 200 million users, Face++ automatically captures faces and detects keypoints on faces, and combines facial expression migration and image fusion technology to generate users' personal comics. , To create a variety of user style. The Raven is an iOS somatosensory interactive game that uses the front camera to capture the player's head movements for game manipulation and is the first head-controlled somatosensory game on the iOS platform. The Raven is an iOS somatosensory interactive game that uses the front camera to capture the player's head movements for game manipulation and is the first head-controlled somatosensory game on the iOS platform. 5. Linkface The world's leading face detection. Linkface provides world-leading face detection and recognition technology services. The accuracy of LFW face recognition has reached 99.5%. 6, SenseTime In September 2014, SenseTime scientists for the first time took part in the ImageNet competition and won the world runner-up at 40.7% in the large-scale object detection competition, second only to Google's 43.9%; in March 2015, the team raised this to 50.3% surpassed Google to achieve the world's top level, and this result was published in the form of papers at the 2015 International Conference on Computer Vision and Pattern Recognition (CVPR). In 2015, ImageNet added a video object detection task that is more difficult to detect than objects in still images. SenseTime teamed up with the team of the Chinese University of Hong Kong Media Lab to set off again. In the end, the team tested two of the world’s top scores in the ImageNet video object detection competition in one fell swoop and tested accuracy, defeating opponents with an overwhelming advantage. Became the first Chinese company to win ImageNet. SenseTime just completed the acquisition of Linkface, another startup company in face recognition technology, at the end of 2015. The latter is also a business black horse, also has many excellent transcripts that surpass the industry. The company's R&D team has more than 50 full-time doctoral positions. The team published more than 150 papers in the top three international top machine vision conferences CVPR, ICCV, and ECCV, ranking first among Asian companies. Dr. Dai Yurong, a two-term chairperson of the ICCV (International Computer Vision Conference) field; more than 80 works published in top-level conference journals; a tenured post in the Korean Institute of Science and Technology (KAIST); an outstanding KAIST 2011 professor; Abandon tenure for joining SenseTime, because he is more interested in SenseTime's ability to transform technology into industry-leading results, as well as his research and development efforts in terms of talent and resources; Dr. Wei Zhang, a college entrance examination scholar from Anhui Province, studied at Tsinghua University and obtained his Ph.D. from the Chinese University of Hong Kong. He was ranked sixth on the Kaggle Data Scientist Rankings and ranked first among Asian scientists. Abandon the hedge fund CTO to join SenseTime. Dr. Sun Wei studied undergraduate education at the Department of Electronics, Tsinghua University and obtained his Ph.D. from the Chinese University of Hong Kong. He is also the inventor of the DeepID series of face recognition algorithms. Surpass the recognition rate of human eyes and beat Facebook. Dr. Bin Zhou, China's first cross-domain R&D senior engineer for HPC (High Performance Computing) and GPU (Graphics Processor). He is the world’s 12th winner of the NVIDIA CUDA Fellow title and is currently the only Chinese scholar to receive this title; Dr. Shirley Qiu, first in the Department of Electronics, Tsinghua University, and Ph.D. from the Chinese University of Hong Kong. In 2014, the DeepID-Net team of Qiu Shi participated in ImageNet's large-scale object detection mission for the first time, with a record of 40.7%. Ranked second, second only to Google. Dr. Shi Jianping, Microsoft Scholar, Google Scholarship, Hong Kong Government Scholarship, from Zhejiang University to the Chinese University of Hong Kong, from the Oral, the first author of the top undergraduate CVPR, to join the entrepreneurial team. Dr. Xia Yan, Ph.D. in computer vision from Microsoft Research Institute, was the first in China National University of Science and Technology, and Guo Moruo received the award. Focus on deep learning, text recognition. Cao Xudong, a deep learning expert. Department of Physics, Tsinghua University, former Microsoft Researcher. Its developed phenomenon-level products such as How Old.net have hundreds of millions of users. This technology is widely used in Microsoft products such as the Xbox. 7, Amscreen The pioneering combination of facial recognition technology and traditional advertising panels came from the European outdoor advertising giant Amscreen. The billboards erected by the company can be seen everywhere in Europe. According to TNW, this bold initiative of Amscreen has been in trial operation for some time. They cooperated with technology provider Quividi to install a “smart eyes†for the “sluggish†billboards. 8. Faceshift Faceshift based on Kinect can map facial expressions in real time to Faceshift facial expression capture tool can feedback your facial expressions to 3D models in real time with almost no delay. Faceshift can make video games, chat, and animated movie production faster and more fun, and it will also give game developers new opportunities. In fact, the SDK for animation and game makers has been released, but of course you can also use it in other areas you can imagine. 9. Robot The first vertical psychological AI emotion caregiver in China, provides each person with anytime, anywhere emotional companionship and active psychological management services. Hill's Advantage: Xiaoqiu is a "warm mound" App related products. Warm hill is currently the most active ordinary person in China's C2C emotional support community. Warm Hill was the first to focus on sentiment corpora in the country. Since September 2014, there are currently 5 million high-quality corpus and it has grown rapidly. Competitive products can make use of public knowledge to make AI, but there is no high-quality corpus, and quality improvement in the later period is a major bottleneck. 10. FeiSheng Technology Co., Ltd. is a high-tech company that applies technological innovation, independent research and development, and applies machine learning, especially deep learning, to face recognition, image recognition, and video content recognition. The real-time face recognition algorithm of Feishou is more than 99.0% accurate on the world's publicly-tested benchmark data set Labeled Faces in the Wild (LFW), which was exceeded after Facebook tested on the same face dataset in June 2014. 97.35% accuracy. It is worth noting that BAT also pulls the switch to face recognition. In 2014, Alibaba Group, which has a family recognition company, will leverage its own platform face data to promote the development of face recognition 2C. At the same time, Tencent has already established a face recognition team internally. Baidu face recognition also rely on huge data resources to progress rapidly. The above rankings come from the Internet, do not represent the views of this site, please pay attention to us more biometric information! Tt5 Timing Belt,Pu Timing Belt T5,T5 Timing Belts,T5 Timing Belt Changzhou Longfu Knitting Co., Ltd. , https://www.nbcircularmachine.com
