DataArt Computer Vision Team To Develop Object Tracking PoC

Responding to a request from a potential customer, DataArt’s R&D department created a prototype application for object recognition and tracking within a video. The customer’s idea for the product was that an object, selected manually in a video for the first time, is then tracked automatically throughout the footage, with the object coordinates retrieved and stored as the video progresses. DataArt’s computer vision scientists and engineers timely conducted a feasibility study, which appeared to be positive, and created a prototype object tracking application. The application allows loading a video, pointing at an object at a specific frame (or again later if the automatic tracking fails), and runs an object tracking analysis over the loaded file. The object is located in the following frames, and the location of the object is stored along with the video as a key-value file, where the calculated coordinates of the object correspond to the current playback time. A commercial playback application could, using this information, then place an ad over the video at these specific coordinates during the playback, thus allowing for dynamic context advertising. film-5  
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DataArt Research Lab to experiment on finding and proofing feature extraction methods suitable for food recognition tasks

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Meals named the same rarely look similar. This is not only due to different people cook differently – in the computer vision sense, meals are combinations of areas (spots) with different color, texture, shape each. This makes typical image recognition principles less suitable for food image recognition, as we cannot rely on either form or relative position of the image parts. Typically, if local peculiarities of objects being detected cannot be caught, integration feature extraction methods take over differential one – e.g. in our current food image classification engine we mostly rely on combined histogram and texture parameters for the whole image. This approach shows relatively good results unless the meal we’re trying to classify appears to have no noticeable texture features.
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DataArt Has Started an R&D Project in Remote Human Pulse Detection, Based on Digital Signal Processing Principles

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Heartbeat Rate app allows to measure the pulse using video processing algorithm
Inspired by recent publication on a video processing algorithm, which is able to detect and magnify subtle periodic changes in color in the series of video frames, DataArt has started experiments on adding heartbeat measurement possibility to their Microsoft Kinect-based healthcare solution. The principle of detection is based on the fact that the human skin becomes more red when the blood pressure is at its maximum (systolic pressure), and less red when the pressure is at its minimum (diastolic pressure). For people not having arrhythmia, these changes are periodic, and therefore, its’ frequency can be caught and measured using spectrum analysis principles.
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DataArt is Building Face Recognition Application for iOS

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To broaden its professional horizons and get involved into something new, DataArt decided to dive into computer vision area, and to be more accurate, face recognition techniques. Our computer vision group created face recognition app that has access to DataArt employees’ database and could recognize them.
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Latest Audio Steganography Techniques on Practice

Latest Audio Steganography Techniques on Practice

Improvements in processor performance of desktop PCs and handheld devices has driven technology to melt chunks of digital information into media streams (an audio file, a TV, radio, Internet broadcast, or an authorized digital content distribution network). The physical principles and mathematics for such techniques were developed long ago; the technical progress is the trigger of making audio steganography a reality. What was considered a ‘spy’ or a secret lab technology ten years ago, is now available to public as a turnkey-quality SDK, or a ready app. This will create more demand and new fields of application.

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Interaction With Wolfram Alpha – New Ideas For Your Business

Interaction With Wolfram Alpha – New Ideas For Your Business

When it comes to business process automation, it’s not a big problem to code the workflow; as business rules can be formulated, and thereby turned into code. But you have to do much more when you need to apply these rules to your business data. In search of the perfect solution DataArt checked the progress with a resource called WolframAlpha that is gaining in popularity.

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iOS Sport Application For Football Fans

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DataArt has finished an experimental iOS-based application that visually recognizes UK football clubs by their emblems. The software identifies club emblems shown on a computer or TV screen, printed in a magazine or a newspaper, or even tattooed on a fan’s chest.
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Augmented Reality on a Gadget

What we typically call an Augmented Reality app on a smartphone or a touchpad device is built the following way: it captures the video stream provided by the built-in camera, transforms it, and delivers the output stream to the screen. The process of ‘transformation’ generally includes detection of a known object (marker) in the input stream, calculating its position in the 3D scene geometry, overlaying the scene with an artificial 3D model, placed at the right position and angles, and putting all this together. Depending on the application, the model can be static or dynamic, interactive or not, etc.
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DataArt Computer Vision Team has Created an All-custom Augmented Reality Engine Prototype

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Augmented reality example in Cactus.AR app
Following a CV-related inquiry, the computer vision team at Dataart created a custom solution for detecting, capturing, and tracking visual markers from a real time video stream. What is usually called Augmented Reality and typically associated with a 3rd party ‘black box’ which does all the complicated spatial job, is now modeled and implemented from scratch by DataArt, with all the 3D mathematics created by researches and ported and implemented by developers.
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