The 5 reference contexts in paper S. Paśko, M. Sutkowski, С. Пасько, М. Сутковский (2016) “ИЗМЕРЕНИЯ АНТРОПОМЕТРИЧЕСКИХ ПАРАМЕТРОВ НА ОСНОВЕ ТЕХНОЛОГИИ ВИЗУАЛИЗАЦИИ ДВИЖЕНИЯ // ANTHROPOMETRIC MEASUREMENT BASED ON STRUCTURE FROM MOTION IMAGING TECHNIQUE” / spz:neicon:pimi:y:2016:i:3:p:305-311

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    The measurements of anthropometric values of the humans’ face are widely used in many different applications, beginning from physical anthropology, medicine (medical analysis, surgery) through security systems (face recognition) to industrial and design (clothing, ergonomics etc.). Most of these values can be determined by use of optical methods
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    [1, 2]
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    . Many of these methods are based on image recognition and image processing. There are divided for two general branches: two-dimensional and 3D data collection [3–5]. Two-dimensional methods are limited by lack of some information (no depth data or only predicted values).
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    Most of these values can be determined by use of optical methods [1, 2]. Many of these methods are based on image recognition and image processing. There are divided for two general branches: two-dimensional and 3D data collection
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    [3–5]
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    . Two-dimensional methods are limited by lack of some information (no depth data or only predicted values). However some of the applications can successfully adopt them (i.e. face recognition) they has some limitations (i.e. impossibility of measure of important anthropometric values).
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    In the paper a very simple imaging system with no calibration demand for anthropometry is presented. The system is based on widely known Structure from Motion (SfM) technique
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    . With use of SfM reconstruction of shape of the object from multiple camera views can be realized. The SfM theorem assume unknown or partially unknown parameters of the camera which may change in time additionally.
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    A series of images taken from fixed points (on the figure points P1, P2, P3 shows few selected camera positions only) is needed. Numerical calculations allow to determine relative 3D coordinates of the object’s points. Collecting data of many points lead to shape reconstruction
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    . 307 markers were placed on the object (patient or examined person). Obviously these markers are needless when the anthropometric measurements would be performed and was applied only for these tests.
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    Obj. – position of the object (patient or examined person); P1...Pn – points where the consequent images was taken from (for convenience only start-point and end-point are marked) Taken images were directed to the reconstruction software which in this case was a VisualSFM v 0.5.25
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    . The calculation was performed on the PC-machine equipped with CPU Intel Core i5 M520@2.40GHz, memory RAM 8GB and operating system Windows 8.1 Pro 64-bit. A series of 42 images was enough to make reconstruction of the 3D model of the scene.
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