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Apr 20, 2017 · More from SautinSoft Team. Convert DOCX file to PDF file in C# (without using MS Office) - Step by Step. 1.6 Star. Convert PDF file to Word file in C# - Step by Step. Convert PDF file to Excel file in C# - Step by Step. Convert PDF file to XML file in C# - Step by Step. Convert DOC (DOCX) file to PDF file in C# - Step ...

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even a nominal distance, especially in crowd surveillance, the face segmentation process tends to be more challenging than other techniques, as there is greater potential for variation The camera s location, field of view, and background setting can introduce considerable variation in how faces occur within the frame and how easy or hard it is to automatically locate and separate the face from the nonface parts of the image frame Location and size differences, if not too extreme, can be corrected once the face is detected and the eyes are located Face detection is accomplished according to shapes and features in the image Most software attempts to find face-like regions of the image by starting from the center and progressing outward The output of the face detection process is location and registration information, consisting of a minimum bounding box for the face, the coordinates of the eyes, and perhaps also the location of the bottom of the nose and the center of the mouth Thresholds for expected intraocular distances can be used to aid the detection process (although that distance varies according to horizontal face rotation) Also, in the case of video sequences, motion information can be used to help locate candidates faces Face detection performance has become very good for single-face images even rotated, off-center faces can be detected and registered for encoding However, the problem is significantly harder when generalized to crowd environments Crowd scenes can contain multiple faces and large variation in distance, camera angle, and pose Additional background motion (noise) can compound the problem further, making face detection performance in these environments much less reliable than in simpler, more controlled, single-face environments Even under less than ideal conditions, reasonable results can be achieved if the software is correctly calibrated and tuned, and cameras are strategically placed in the target environment Some, but by no means all, of the software calibrations necessary for a particular environment can be configured by knowledgeable operators and system integrators More dedicated calibration efforts could involve modifying the software or adding custom markers in the environment Markers provide depth queue information to the otherwise flat images and can also help disambiguate some occlusion problems that arise in crowd situations The commercial face recognition techniques discussed here are all designed to work best on straight 2D frontal images, or mug shots Plausible approaches to the problem were researched and explored by universities during the 1980s, and the first generation of moderately successful approaches began to surface in academic literature in the late 1980s and early 1990s These first examples of the technology operated in minimally constrained environments and only performed well on a small number of individuals and a limited set of images 1996 was an important year for facial recognition, as it was the year of the first government FacE REcognition Tests (FERET)1 The 1996 FERET tests were sponsored by Army Research Laboratories and designed and orchestrated by.

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C#.NET code to convert PDF to Word - Yiigo
This document provides comprehensive Visual C#.NET samples for guiding developers to convert PDF to Word using Yiigo.Image for .NET.

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C#.NET code to convert PDF to Word - Yiigo
This document provides comprehensive Visual C#.NET samples for guiding developers to convert PDF to Word using Yiigo.Image for .NET.

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How to convert PDF to Word programmatically in C#
How to convert PDF to Word programmatically in C#. If you are looking for a good solution for converting PDF files to a Word (.docx or .rtf) programmatically, ...

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