50 research outputs found

    Packet-based Hierarchal Soft Shadow Mapping

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    International audienceRecent soft shadow mapping techniques based on back-projection can render high quality soft shadows in real time. However, real time high quality rendering of large penumbrae is still challenging, especially when multi-layer shadow maps are used to reduce single light sample silhouette artifact. In this paper, we present an efficient algorithm to attack this problem. We first present a GPU-friendly packet-based approach rendering a packet of neighboring pixels together to amortize the cost of computing visibility factors. Then, we propose a hierarchical technique to quickly locate the contour edges, further reducing the computation cost. At last, we suggest a multi-view shadow map approach to reduce the single light sample artifact. We also demonstrate its higher image quality and higher efficiency compared to the existing depth peeling approaches

    Predicted Virtual Soft Shadow Maps with High Quality Filtering

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    International audienceIn this paper we present a novel image based algorithm to render visually plausible anti-aliased soft shadows in a robust and efficient manner. To achieve both high visual quality and high performance, it employs an accurate shadow map filtering method which guarantees smooth penumbrae and high quality anisotropic anti-aliasing of the sharp transitions. Unlike approaches based on pre-filtering approximations, our approach does not suffer from light bleeding or losing contact shadows. Discretization artefacts are avoided by creating virtual shadow maps on the fly according to a novel shadow map resolution prediction model. This model takes into account the screen space frequency of the penumbrae via a perceptual metric which has been directly established from an appropriate user study. Consequently, our algorithm always generates shadow maps with minimal resolutions enabling high performance while guarantying high quality. Thanks to this perceptual model, our algorithm can sometimes be faster at rendering soft shadows than hard shadows. It can render game-like scenes at very high frame rates, and extremely large and complex scenes such as CAD models at interactive rates. In addition, our algorithm is highly scalable, and the quality versus performance trade-off can be easily tweaked

    Robust region‐wise colour correction method for stereo matching

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    Significant colour discrepancies between stereo images have severe impacts on stereo matching algorithms, which depend on colour similarity. To address this problem, a region‐wise colour correction method is proposed in this study. First, the source image, which is to be corrected, is segmented into a set of regions using the mean‐shift method. Scale invariant feature transform (SIFT) features are extracted from both the source image and the reference image, and then matched. The matched SIFT pairs are refined by exploiting epipolar geometry constraint. Based on the segmentation result and the refined SIFT matches, the regional correspondences between two stereo images are estimated. Then, each matched region pair is used to compute a local colour correction function. A set of colour weight maps is calculated for these functions. Finally, to alleviate the colour transformation discontinuities along the region boundaries and facilitate a smooth colour correction globally, the corrected colour is obtained by combining the colour correction functions using the colour weighting maps. The authors apply the proposed local colour correction method to stereoscopic images before conducting stereo matching. The results indicate that the proposed algorithm can effectively and robustly alleviate the colour discrepancies, and improve the accuracy of stereo matching

    Visual saliency guided normal enhancement technique for 3D shape depiction

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    Visual saliency can effectively guide the viewer's visual attention to salient regions of a 3D shape. Incorporating the visual saliency measure of a polygonal mesh into the normal enhancement operation, a novel saliency guided shading scheme for shape depiction is developed in this paper. Due to the visual saliency measure of the 3D shape, our approach will adjust the illumination and shading to enhance the geometric salient features of the underlying model by dynamically perturbing the surface normals. The experimental results demonstrate that our non-photorealistic shading scheme can enhance the depiction of the underlying shape and the visual perception of its salient features for expressive rendering. Compared with previous normal enhancement techniques, our approach can effectively convey surface details to improve shape depiction without impairing the desired appearance
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