Computer Vision Developer
Computer Vision Developer

We are looking for an experienced and dedicated software engineer with a strong mathematical background, ability to solve challenging technical problems in image processing and computer vision. Key responsibilities are development of image and signal processing algorithms, reading and implementation of state-of-the-art papers, R&D activities. Main research directions are pattern recognition, object tracking, detection and recognition.

Deep Learning Engineer
Deep Learning Engineer

We are looking for an experienced and dedicated data scientist with a strong mathematical background, ability to solve challenging technical problems using machine learning and deep learning in image and video processing domains. Key responsibilities are development of ML/DL models for analysis of visual information (object detection and recognition, object tracking, image segmentation), reading and implementation of state-of-the-art papers, R&D activities.

Light-Weight Tracker for Sports Applications

In the paper, we describe technical details of multi-player sports tracker system. We demonstrate that proper in-depth analysis of video frames  sequence may provide a lot of useful information required for sports  analytics. Object detection and tracking steps are analyzed. Novel ideas for efficient filtering of false detections and irrelevant tracks are proposed.

Outdoor Mapping Framework: from Images to 3D Model

3D mapping techniques have a large variety of applications from entertainment to military and medical fields. However, there is a big challenge of obtaining well refined 3D model from a set of images without usage of depth sensors. In the paper, we analyze main components of 3D reconstruction pipeline allowing to get detailed models of outdoor objects from drones. In particular, we experiment with algorithms required for structure from motion and point cloud densification.

Mobile Indoor Navigation: From Research to Production

Indoor positioning systems in GPS-denied environments are rapidly becoming popular. Various options are commonly available (BLE, Wi-Fi, ultra-wideband, ultrasonic, etc.). The key challenge is to provide accurate, and stable real-time user location at a low cost. In this paper, we present the research and production details of the developed hybrid indoor localization and navigation system (HILN). The proposed technical solutions are based on cheap Bluetooth beacons and mobile sensors.

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Automatic document analysis and recognition is a hot topic in a modern computer vision. A common scenario is when the user takes a picture by mobile phone or tablet and the goal is to automatically parse and recognize content from the captured document. Such like pictures, tables, text data, links, etc. There are several challenges in this case: geometric distortions of the paper, varying illumination, occlusions.