Shadow Map Construction using 2D Homography

In computer graphic applications, shadow plays an important role in expressing the reality of an object. Shadow shows the relationship between objects in space. Shadow map is one of the methods that meet the demand simplification in implementation and speed. This method made an alias around the border of shading. In this paper, we proposed a method using a 2D homography transformation. This method reduces the unused area in the shadow maps, so it can help to minimize the alias. With the experiment in VanMieu Tran Bien- a Vietnamese historical place, we compare the method with others.

Interactive 3D Time-Integrated Solar Shadow Maps

<p><strong>Abstract.</strong> Urban areas are characterized by a complex topography of buildings, terrain, vegetation and temporary structures, which, depending on their extent, geometry, geographic location and daytime, cast shadow on their surroundings. Given the importance of sunlight for various groups of interest and tasks, we argue that a comprehensive, accessible, usable and intuitive way of predicting its availability for specific usage contexts is surprisingly lacking. In our research, we are investigating how to improve the visual communication of urban solar conditions for various real-world usage scenarios like having a coffee in the sun, parking a car in the shade, or taking a photograph of a particular building in a favorable light. All of these activities take place over a period of time, not in a temporal instant, causing solar shadows to move. Hence, a static representation of the light situation at a distinct point in time, such as offered by available 3D urban maps or GIS systems, is often not sufficient for planning above mentioned recreational or professional activities.</p><p>This factor is incorporated in our system by integrating shadow motion into a shadow map that covers arbitrary timeframes within a given day (Figure 1). Shadows are accumulated by projecting shadow maps from astronomically precise sun positions spanning over the defined timeframe. The number of sampling points directly influences the quality and speed of the rendering. All provided figures currently sample and integrate nine different sun positions.</p><p>Using our system, questions in a manner of “Given a specific point in space, at which time will this point be in sun/shade again” can be answered. E.g., one would like to spend time in the sun at a specific Viennese “Kaffeehaus” (coffee place), from which time on (and for how long) will this space be sunlit (Figure 2). In the future, this process might even be automated.</p>

SHADOW DETECTION FROM VERY HIGH RESOLUTON SATELLITE IMAGE USING GRABCUT SEGMENTATION AND RATIO-BAND ALGORITHMS

Very-High-Resolution (VHR) satellite imagery is a powerful source of data for detecting and extracting information about urban constructions. Shadow in the VHR satellite imageries provides vital information on urban construction forms, illumination direction, and the spatial distribution of the objects that can help to further understanding of the built environment. However, to extract shadows, the automated detection of shadows from images must be accurate. This paper reviews current automatic approaches that have been used for shadow detection from VHR satellite images and comprises two main parts. In the first part, shadow concepts are presented in terms of shadow appearance in the VHR satellite imageries, current shadow detection methods, and the usefulness of shadow detection in urban environments. In the second part, we adopted two approaches which are considered current state-of-the-art shadow detection, and segmentation algorithms using WorldView-3 and Quickbird images. In the first approach, the ratios between the NIR and visible bands were computed on a pixel-by-pixel basis, which allows for disambiguation between shadows and dark objects. To obtain an accurate shadow candidate map, we further refine the shadow map after applying the ratio algorithm on the Quickbird image. The second selected approach is the GrabCut segmentation approach for examining its performance in detecting the shadow regions of urban objects using the true colour image from WorldView-3. Further refinement was applied to attain a segmented shadow map. Although the detection of shadow regions is a very difficult task when they are derived from a VHR satellite image that comprises a visible spectrum range (RGB true colour), the results demonstrate that the detection of shadow regions in the WorldView-3 image is a reasonable separation from other objects by applying the GrabCut algorithm. In addition, the derived shadow map from the Quickbird image indicates significant performance of the ratio algorithm. The differences in the characteristics of the two satellite imageries in terms of spatial and spectral resolution can play an important role in the estimation and detection of the shadow of urban objects.