Trueface computer vision wins for biometric travel innovation, public safety
The National Institute of Standards and Technology (NIST) has announced Trueface, CalAster and several academic teams as Phase 1 winners in a computer vision challenge it is hosting in partnership with FirstNet. Titled ‘Enhancing Computer Vision for Public Safety’, the aim of the challenge is to help develop a new line of research in computer vision to develop life-saving tools for public safety and first responders. The challenge seeks computer vision experts to create innovative solutions to these impairments that CV systems face, with a $240,000 prize.
NIST launched the challenge in September, and the Phase 1 winners are now in the six-month development phase ahead of the dataset submissions due date of May 4, 2021. Other winners include teams from the Laboratory for Imaging and Video Engineering (LIVE) from the University of Texas at Austin, the New Jersey Institute of Technology’s iAI Tech, and IUPUI.
The introductory video describes computer vision’s “super human efficiency.” Often in emergency situations, such that first responders face, computer vision systems can be disproportionately affected by weather conditions, like snow. The first goal of the challenge is to create datasets showing impairments that impact CV, and secondly to develop methods to estimate the failure rate of computer vision algorithms. Hoping to result in a better research capacity of CV algorithms, and image quality analysis for public safety. Those that win the challenge will have the opportunity to provide training datasets to computer vision research communities.
An example solution is an algorithm that could go between the camera and the computer vision algorithm. This algorithm would assess the image or video quality; such as zooming, panning or changing the bit-rate.
Full challenge details are available at Challenge.gov.
Trueface wins pitch for biometric travel innovation
Trueface has also delivered a winning pitch at PhocusWright’s innovation conference, reports PhocusWire. Trueface won both the Innovation Summit: People’s Choice Travel Innovator Of The Year and Most Innovative Startup awards.
The company “teaches cameras to see like human beings” says CEO Sean Moore in the pitch. Trueface is aiming to smooth out the process of the customer journey through travel, starting by using technology which is already in play in airports.
This is a reaction to the pandemic, by helping the sector open up again in a secure way, and reassuring travelers in doing so. Some examples of Trueface’s technology in this instance include; elevated temperature checks and PPE compliance, as well as flow of foot traffic.
Trueface’s CV technology is able to process a billion faces per second (that would be the world’s population in approximately 8 seconds). The company aims to reduce error rates within facial recognition, while ensuring not to discriminate between ethnicity or gender, and maintain ethical data use and security — three prominent issues within facial imaging technology.
Grand View predicts massive computer vision market growth
A report published by Grand View Research predicts the computer vision market to grow from its valued $10.6 Billion in 2019, to $19.1 Billion by 2027 – at a CAGR of 7.6 percent.
Computer vision’s popular systems include biometric scanning and facial recognition, particularly within security systems. These systems are proving to be some of the main drivers of market growth. The use of computer vision in self-driving cars is also expected to boost the growth in the market.
The Asia Pacific dominated the market and accounted for over 38.0 percent share of global revenue in 2019, states the report. This was due to increasing investments in Chinese companies for computer vision technology. Meanwhile CV software is expected to demonstrate a notable shift in its demand, registering a CAGR of 8.6 percent over the forecast period. The report further notes some of the key players in the CV field as Cognex Corporation, Intel Corporation, Keyence Corporation among others.
Computer vision capabilities have been growing rapidly with the use of deep learning techniques in not only replicability of human vision, but surpassing human vision in terms of pattern recognition. This movement has proved to be cutting edge in the monitoring of the coronavirus outbreak.
The techniques have been used in medical data monitoring to diagnose patients and traffic control in urban spaces. AI-enabled computer vision can be used, for example, as imagery solutions in consumer drones and autonomous and semi-autonomous vehicles. These developments mean that computer vision can be applied to several industries including education, healthcare, robotics, consumer electronics, retail and manufacturing.
The report also notes innovative examples of companies who are leading the way in the field, including Canadian start-up BlueDot, which uses advanced data analytics to anticipate infectious disease risks and coordinate emergency response using public health and medical expertise, and Nurmina, a U.S. based start-up that utilizes computer vision tools for the development of sustainable cities.