Total ETH raised:
Tokens sold: 214,383,477 FACE
Total ETH raised:
Tokens sold: 214,383,477 FACE
Video surveillance systems are currently the most efficient technical tool to ensure public safety by the means of recording facts and controlling the situation at any site.
Current problems in the field of video surveillance
Faceter’s solution – what makes it so awesome
Faceter is a system which makes video surveillance smart by giving eyes to cameras — computer vision, facial recognition, object detection and video content analysis in real time. In the next stage, all these abilities will be combined into one — “understanding” the situation and then reacting to it. We call this concept “event security model”.
Greatly enhances the capabilities of video surveillance systems to detect potential threats or such events as a smiling customer, a focused employee, etc.
The cost of the product is significantly reduced by involving cryptocurrency miners into a decentralized computing network to perform recognition calculations with the added benefit of offering miners a higher income–earning opportunity.
Using neural networks, you can teach Faceter to react on variations of certain events.
Faceter does not process the source video stream outside its trusted environment; only anonymized data is transferred to decentralized networks.
Faceter uses all the nascent opportunities of smart contracts to deliver flexible and transparent payment options and as well as proof–of–recognition mechanisms to a Fog computing network. This is the way Faceter contributes to the growth of the crypto-industry.
The Faceter token is the “fuel” of a decentralized network enabling flexible, transparent, cross-border closed-loop settlement mechanism for all participants.
Faceter transforms ordinary cameras into advanced security systems that “understand” what’s going on with fast, accurate, and efficient facial detection and recognition. It enables a new level of service for your security needs.
Cryptocurrency miners can rent their equipment to Faceter and make more money than they would by mining. They’ll make money 2.5 times more quickly than mining Ethereum, and 5 times more quickly than mining Monero. Faceter will use a decentralized infrastructure to reduce computing costs.
The product is ready for B2B customers and has been tested in three successful proofs of concept. The team has clear plan for development the mass market version, which means that FACE tokens stand a chance to be put to intended use within a timeframe set in the project’s roadmap.
Video stream analysis requires immense computing power. We are planning to build a decentralized network that implements fog computing, drastically reducing the price of our product to make it affordable for homeowners and business owners around the world.
The token is the core of the decentralized network, both as a Proof of Recognition and a flexible, transparent, cross-border settlement mechanism for all participants. It is the cryptocoin for payments we get from customers. Work of participants in our decentralized network is paid by tokens as well.
February 5, 2018 – February 15, 2018
Tokens to sell:108,000,000 FACE
Bonus program:50%, 40%, 30%, 20% determined by whitelist position. Extra 5% bonus for individual purchases greater than $10,000
February 15, 2018 – March 30, 2018*
Tokens to sell:300,000,000 FACE
Bonus program:20% for early contributors only
Soft cap:50,000,000 FACE
Buyback & Burn, Miner rewards, License issuance
1000 FACE = 0.0872 ETH
All tokens that will not
be sold through the
token sale will be
Token Delivery Date:
1 week after closing
Total token supply1,000,000,000
An international team with extensive R&D experience at computer vision, as well as managing a high-tech international business.
Fulfilling Sci-Fi Predictions
Alpha version of Faceter for B2B is released
Proof-Of-Concept of Faceter for mass-market (centralized version)
Building modular architecture and adapting Faceter to fog computing networks to reduce computation costs
Developing Android, iOS, Apple TV applications
Developing a module for classifying individuals in videos to augment the event-based model with the following features: sex, age, race, emotions
New team members: growing IT department
Launching beta version of Faceter running on a fog and starting sales in the mass market segment
Adding a “user friendly” option: store video archives in decentralized IPFS-based storage providers
Developing integrated solutions in collaboration with hardware vendors
Tracking visitors with partially or completely hidden faces. Recognizing body type features: height, weight, build
New team members: sales and business development specialists
Vehicle detection and recognition in video, including recognition of numbers using cameras with sufficient resolution
Partnership agreements with video camera vendors regarding Faceter preinstallation
Developing a technology for detecting different events in the cameras’ scope: run, fall, fight, unattended items, hazardous situations (flame, smoke, vibration, non-standard noise etc.)
Launching a fully functional decentralized version of Faceter
Singapore – 5-6, February 2018.
As a centrally-located hub in South-East Asia, many local and nearby neighbors had the opportunity to visit the Forum. The region is well known for its cryptocurrency and Blockchain knowledge and are usually very well informed of the potential of the market.
San Francisco, London, Amsterdam
In January the Faceter team is taking part in the global road show CryptoEconomy.
The conferences and exhibitions in the first round will be arranged in three cities: San Francisco, London and Amsterdam, and in each of them you will have a chance to communicate with members of our team.
Moscow, Russia – December 2017
We visited the conference — CryptoSpace 2017 in Moscow and met a lot of interesting people. We discussed our plans with Miko Matsumura (Miko Matsumura) and had talks with many other brilliant people
We use blockchain in three different ways:
We need a decentralized infrastructure because it will help us to provide a consumer version of our solution and make our product affordable for homeowners and small businesses globally. Facial recognition and computer vision technologies are very expensive because they consume a lot of computer resources. As I mentioned we have a working solution and we have interest of potential business users. But current classic infrastructure architecture can't be used for providing mass market solution – it is too costly. So, we will develop our solution to be able to pass the processing work over to existing miners in the blockchain industry. This decentralization will drastically reduce the price of the solution. Even if we offer Ethereum miners 5 times more than they are currently getting to mine cryptos, it will be still financially feasible for us. With PoS becoming more popular there is a growing concern for miners as they have the hardware but mining less as mining pools continue to get larger and more demanding.
In the future, smart-contracts with customers can also become part of collective security network, integrated with police databases. So that police will be able to distribute pictures of wanted criminals, lost kids, stolen cars and so forth.
Yes, it is a necessary part of our business model. It is the main cryptocoin for payments which we get from customers and which we send to participants of our decentralized network. If customer pays by fiat money, we convert them into Faceter tokens via ShapeShift-like exchange.
We have market-ready product for business customers – they can buy it by classic software license and install it on-premise. The technology is tested in real life situations in three PoC projects: in casino, in Debonairs pizzerias (one of the most popular fastfood chain in South Africa) and in plant. All potential customers gave a good testimonials and are eager to sign-up agreements. The PoC project was realized with our partner – EPI-USE, exclusive representative and distributor of SAP in South Africa. We successfully integrated Faceter into SAP ERP business system. Faceter is also certificated by Axis (one of the biggest global video camera manufacturer), it means that software was tested in Axis cameras and showed high level of compatibility.
Our computer vision algorithm for facial recognition shows 99,78% accuracy (top-6) according to LFW benchmark and 79.46% (top-10) by MegaFace.
On the next stage of project development, we will build decentralized network. It will allow us drastically reduce cost on infrastructure and bring our computer vision technology for intellectual surveillance to the mass market.
CTO and one of the founders of Faceter Vladimir Tchernitski has more than 25 years of experience in software development. Before Faceter he was the head of R&D-department of international outsource software development company, where he started to work with convolutional neural networks, more than 4 years ago. The current Faceter’s team, by guidance of Vladimir, has already developed a successful product – opensource library pay.cards for banking cards data recognition, which became very popular among mobile application developers worldwide and was downloaded more than 25 000 times.