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Making perspective images using graphics programs
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| bet | 1/3 | | Sana | 22.11.2022 | | Hajmi | 105.68 Kb. | | #31293 |
Bog'liq Making perspective images using graphics programs. diskret odilshox, elektronika va sxemalar (mustaqil ish), Обективка Шахzod 2022.й, Alohida tayanchlar 01, S. Hasanov - Materiallar qarshiligidan masalalar yechish, moliya maruza
MAKING PERSPECTIVE IMAGES USING GRAPHICS PROGRAMS.
Sheraliyev Sanjarbek Karimberdiyevich
1styear master's degree Tashkent State Pedagogical University
Named after Nizami, Engineering Graphics and Design Theory Faculty
ssh19902310@gmail.com
ANOTATION.
This research paper meant to analyze several methods of creating perspective images in some useful graphics programs. Multi-perspective images are a useful way to visualize extended roughly planar scenes such as landscapes or city blocks. However, constructing effective multi-perspective images is something of an art.
Key words: image editing, perspective image, Adobe, Computer Graphics Programs.
INTRODUCTION.
Perspective artist's work to ensure the correctness of the structure of the picture, to check and correct the composition of the building under construction at the design stage, to determine the size of the object through aerial photography, to restore the movement of previously colliding mechanisms in criminology, as well as , used in optics and other fields.
Probably due to the relatively low number of categories for perspectives, the correlation analysis showed a correlation between all of them. On the other hand, some relationships have proved to be stronger than others are. An example is a category of Clarity that has a high impact on the First Impression(R = 0.72) as well as the Space and Massing(R = 0.78) and the Overall Rating (R = 0.81). This finding shows the need for a clear presentation of the perspective for an independent observer that easily understands where the perspective standpoint is located in the project. At the same time, it confirms that the need to think carefully about the entire scene and appropriate choice of the view into the main composition spaces are crucial in perspective views. Further results have confirmed that the characteristics of objects and surfaces are the domain of hand-based techniques. The hand can free and quickly illustrate floors and windows of objects or hatching the surfaces and pavements. Correlation has shown that in digital visualizations the detail focused on the staff age such as people, cars or greenery and miss the object and surface finishing and details.
Visualization of cities and urban landscapes has been a theme in western art since biblical times. The key problem in making these visualizations successful is summarizing in a single image the extended linear architectural fabric seen at eye level along a possibly curving or turning street, and doing so without introducing excessive distortions. In this paper, we address this problem. Possible applications include using these visualizations for in-car navigation, an augmentation to online route mapping applications, and web based tourism information. One possible approach to depicting the eye level urban fabric is using wide angle or omnidirectional views around a single viewpoint, typically captured at street corners. Omnidirectional cameras [Nayar 1997] provide a possible optical solution for capturing such views. Photo mosaicking (the alignment and blending of multiple overlapping photographs) is an alternative approach for creating wide field of view images. These mosaics can be made by capturing a part of the scene surrounding a single point by panning a camera around its optical center [Chen 1995; Shum and Szeliski 2000]. However, such omnidirectional views are still perspective projections and therefore, objects at any considerable distance from the camera become too small to be recognizable. A set of such views, each taken at more closely spaced intervals along the street, overcomes this limitation. However, such a set still fails to capture the linear nature of most urban fabrics and its continuity as experienced by a motorist or a pedestrian. Another possible approach is to use push broom [Hartley and Gupta 1994; Peleg et al. 2000] or cross-slits imaging [Zomet et al. 2003]. A push broom image is defined as an image that is perspective in one direction (e.g., vertically) and orthographic in the other while a cross-slits image is an image which is perspective in one direction but is perspective from a different location in the other direction. The perspective structure of cross-slits cameras are the set of all rays intersecting two fixed lines (slits) in space. For push broom cameras, one of the slits is at infinity. In both cases, one is free to select the placement of the slits. Changing these placements strongly affects the visualization and the associated distortions as we show later in our results. In the context of visualizing eye level urban landscapes, we show that we can combine multiple cross-slits images seamlessly to reduce distortions. Our main contribution is that we describe an interactive system for constructing multi-perspective images from sideways-looking video captured from a moving vehicle. The input to our system is a set of video frames with known camera pose. The interface then provides a set of tools that allow the user to define the picture surface and place cross-slits cameras. Our system then automatically computes an additional cross-slits camera between every pair of adjacent user-specified cameras leading to a smooth interpolation of viewpoint in the final multi-perspective image. Our system provides the tools necessary to minimize distortions and discontinuities for creating good multi-perspective images for urban landscapes. Using our system, a person can create a multi-perspective image of a whole city block in a few minutes. The process is summarized in the below figure.
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