NVISO Insights app for iOS has been released to the Apple Store

The new NVISO Insights app for iOS has been released to the Apple Store. The app demonstrates the visual intelligence technology behind NVISO’s Insights DEVELOP Software Developer Kit (SDK): this will empower developers to embed artificial intelligence into their applications. The app creates digital experiences with enhanced levels of safety, security, and personalization through real-time analysis of human behaviour, in live camera feeds and pre recorded images and videos.

From the app main menu it is possible to select:

  1. Object Detection: this showcases NVISO object detection capabilities with a demonstration that detects human faces.
  2. Emotion Recognition: this allows you to analyse a person’s emotions in real-time based on their facial expressions using the camera on the device.

Users can switch between the front and rear-facing cameras and also analyse pictures and videos stored on their devices.

What is visual intelligence? 

Visual intelligence is the ability of a machine to see and understand things the same way humans do. Computers don’t have brains and feel no emotion. They don’t have the ability to form opinions or to think subjectively. But they can learn by visual examples and visual examples can enable machines to mimic those qualitative things to help us improve. With visual intelligence, computers are able to interpret things the way humans see them.

How does it work? 

NVISO’s visual intelligence technology uses computers to learn from examples as opposed to being manually programmed. Using deep Convolutional Neural Networks (CNNs) and state-of-the-art machine learning to understand human behaviors depicted in images and videos, it can achieve accuracy levels that surpass human performance in many narrowly defined tasks.

What is the potential? 

NVISO uses large training datasets containing millions of samples with proprietary software to detect, analyze and interpret behaviors from different learning scenarios (emotions, face, identification, semantics, etc.). By continuously improving our datasets, training our algorithms, and benchmarking, we constantly expand the scope of applicability for visual intelligence in different industries.



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