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The task of automatic document analysis and recognition is very common in everyday life. Basically, every time when a user needs to automatically parse and recognize some content from a picture captured with a mobile phone/tablet or a scanned document – for example, text, tables, links, etc., automatic document recognition and text analysis come to the stage.

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Planar Tracker for Augmented Reality
Planar Tracker for Augmented Reality

Marker-based augmented reality (AR) is extremely popular nowadays. However, full user immersion is possible only in the case of robust real-time computer vision solutions working on the mobile device. We have developed a custom hybrid tracking system based on local feature tracking and template-based matching. The tracking engine tracks the homography changes using optical flow algorithm and then refines the residual warp using the optimized template matcher.

Object Recognition in Radar Images

Object recognition is an important computer vision and machine learning problem. A particular case is automatic target recognition (ATR) on radar images. In the project, our team has developed a custom classification algorithm based on two different tools. We have been working with MSTAR dataset. This is a public dataset containing ten classes of vehicles with different orientations with 0.3mx0.3m.

Object Recognition in Radar Images
Binary Marker Recognition on Raspberry
Binary Marker Recognition on Raspberry

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 Engine

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.

Indoor Positioning Engine
High-performance Autofocusing for Synthetic Aperture Radars
High-performance Autofocusing for Synthetic Aperture Radars

Synthetic aperture radar (SAR) systems are very popular instrument for high-resolution image of ground surface. Unlike to optical systems, SAR can be used in all weather and lighting conditions. A basic idea of SAR technique is coherent processing of received signals on a moving platform (aircraft or satellite). The main challenge is to perform very precise measurements of platform position at each moment of time.

Road Detector
Road Detector

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.