Augmented reality has already proven its positive impact on many businesses. One of the latest trends is so-called WebAR. Indeed, what can be easier than just opening the web page for instant immersive experience? The goal of this project was to develop and optimize the image detection and tracking algorithm for AR applications. The main challenge was to make it work directly in the mobile web front-end with all computations done on the edge.
Our client’s goal was to enhance various printed media (magazines, posters, banners, etc.) with interactive experience using augmented reality. With AR, certain areas on the reading materials can be overlayed with digital information of a different kind: from videos, images, and 3D models to weather information and buttons that bring additional functionality, etc.
Object recognition is an important computer vision and machine learning problem. A specific case is automatic target recognition (ATR) on radar images. ATR can be effectively used for border security, safety systems to identify either man-made objects (such as buildings, ground and air vehicles) or people, as well as for target surveillance. In other words, with ATR one can obtain any visual information about the ground and objects without direct physical contact.
Indoor positioning systems are becoming popular nowadays. Indeed, there is plenty of opportunities for real-time user navigation in GPS-denied environments. An interesting use cases are as follows: Fig. 1. Indoor navigation use cases There are several options for hardware (see It-Jim blog post). We have developed the positioning algorithm based on cheap Bluetooth beacons and built-in IMU sensors on mobile device.
Our task was to develop the algorithm for the automatic road detection in radar images. The challenge was that the radar images are a bit different from the optical ones. In particular, in the case of synthetic aperture radar (SAR), the image formation process is accomplished via coherent processing of the received signals backscattered from the Earth surface. As a result, the multiplicative speckle noise appears in the SAR images.