Dimples and pimples, lip curves, and eye wrinkles—all these elements make a person’s face distinctive. Face analysis technology helps you learn more about your users, valuable knowledge you can then translate into more personalized user experiences.
Being a leader in customer experience (CX) pays off. But according to Accenture, a focus on CX may not be enough. Instead, top innovators who “push beyond the CX philosophy and organize the whole business around the delivery of exceptional experiences” outperform their peers in terms of year-on-year profitability growth by 6.5 times. To offer these types of exceptional, personalized, and interactive experiences you need reliable and ethical face analysis technology that provides the speed, accuracy, and performance your customers desire.
The speed of technology affects customer satisfaction, engagement, and retention rates, and face analysis technology is no exception. In industries such as automotive and healthcare, facial analysis speed is clearly a crucial operational requirement, where delays in response can lead to dire outcomes.
Latency has a huge impact on the performance speed. Sending data from a remote device to a cloud or remote system and back to the user adds extra processing time. To mitigate this, AlgoFace’s technology executes face analysis processing on the edge. This means it can perform face analysis straight from the end-users device without relying on the quality of the internet connection, considerably improving performance speed and providing greater user privacy.
At AlgoFace, our FaceTrace technology has achieved very high speed on the edge devices such as Raspberry Pi, Nividia Jetson, Mobile Phones and even inside a browser. We accomplished this by first building a tiny size machine learning model using different techniques. Then we optimize the model for both CPU and GPU for each platform that we support. This directly contributes to higher technology performance speed.
If not done properly, face analysis can become problematic. We’ve seen and read news stories about skewed AI models that falsely identify, or make incorrect assumptions, about certain groups. Facebook recently had to publicly apologize when their AI algorithms wrongfully suggested that users may be interested in watching more videos about primates, after viewing a clip with Black men.
Why do such shameful misidentifications occur? Because many algorithms are trained on homogenous, limited datasets, and these models are more likely to be inaccurate which leads to underrepresented or even misrepresented groups.
But this problem is not a foregone conclusion. The world today has wonderfully diverse faces. AlgoFace is focused on building highly accurate, diverse, and inclusive face analysis solutions. What’s more, we use 209 facial landmarks to accurately interpret the unique features of people’s faces. This way, all types of users can equally benefit from the immersive augmented reality (AR) experiences you create.
The Cost of Face Analysis
The cost of incorporating face analysis technology into your product or platform can vary greatly because of numerous contributing factors. Let’s tackle direct costs first. When it comes to AI model development timelines, 40% of enterprises with mature AI spend at least 30 days deploying machine learning/deep learning models into production. Mind that this stat only mentions “deployment” rather than the entire development lifecycle which requires algorithm development, training, validation, and quality assurance (QA). Clearly, the full cycle from development through deployment takes significant time. In our case, we offer ready-to-deploy solutions, which can be launched quickly with minimal infrastructure configuration on your end. Likewise, our software development kit (SDK) eliminates the expenses associated with model development, training, and quality assurance. Faster time to market is a good bargaining chip for persuading stakeholders, but there’s more to it than just that. High-performance face analysis models also drive indirect business gains which offset costs, such as:
- Exceptional experiences: Over 50% of consumers would love to use augmented reality for assessing products. Data from Shopify also suggests that the conversion rate for products with AR content is 94% higher than for products without it.
- New sales channels: From selling age-sensitive products through vending machines to offering digitally powered in-store beauty bars, face analysis software can augment, or even create entirely new sales channels, enabling new ways of distributing products to your customers.
Preparing for Face Analysis Technology Implementation
When it comes to rollout, we work with you based on your product goals, budget, and technical considerations. Whether we are providing you with an already developed SDK or assisting in the creation and development of an entirely new product, our job is to to develop infrastructure for your business that is conducive to speed and accuracy at a reasonable cost.
This entails :
- Determination of deployment scenario. Do you plan to run the software locally, in the cloud, or on a connected device? In each case, ensure that you provision sufficient resources for effective operations. We can advise on the right sizing.
- Assess your data processing infrastructure. Our SDK works with RGB cameras and connects with popular cloud-based data lake and data warehouse services. However, you have to ensure secure endpoint integration and unconstrained data processing to prevent latency issues.
- Consider scaling approaches. Do you expect some heavy-duty usage? Our algorithms are built for scale but require supporting IT infrastructure. If you plan to connect multiple cameras or use large databases (think 1TB+), performance speed may go down—unless you implement load balancing and parallelization, for instance.
Fast, Right, and Cost-Effective: Doable With AlgoFace
We designed our face analysis technology to be nimble and mingle well with different deployment scenarios. Is it the cheapest solution on the market? No, but it comes with an unbeatable price-to-value ratio. We can track three times more facial landmark points than other industry players utilizing diverse and inclusive datasets while also offering the highest levels of privacy to your customers.
Fast and accurate face analysis technology comes at a cost, but we offer the perfect blend. To learn more, request a free FaceTrace SDK demo today.