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.
Fiducial markers are widely used in various applications like robot navigation, logistics, augmented reality. Fig. 1. Applications of fiducial markers Advantages are obvious High contrast Simple code generation Resistance to extremal angles However, when we deal with a large number of markers, real-time recognition becomes challenging, especially on embedded devices with low power CPUs on-board.
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 a mobile device.
