Posing a digital character by acting on the vertices of a coarse control cage is, after skeleton-based, probably the most widely used technique for digital animation. While skeleton-based techniques have been deeply researched and a variety of industrial and academic tools are available for it, cage-based techniques have historically received less attention. In recent years we observed an increasing interest in the field, which results in a growing number of publications both on algorithms for automatic or semi-automatic cage generation, and for smooth barycentric coordinates for general polyhedral meshes. We introduce CageLab: a novel research-oriented software tool that allows scholars and practitioners in general to get acquainted with cagebased animation in a lightweight and easy to use environment. Users can: (i) load digital characters and their associated cages, applying character deformations with a selection of the most widely used barycentric coordinates available in literature; (ii) compare alternative cages for a given digital character; (iii) compare alternative barycentric coordinates w.r.t their smoothness and locality within the cage; (iv) use CageLab for educational purposes, or to produce images and videos for scientific articles. We publicly release the tool to the community, with the hope to support this growth, and possibly foster even more research in the field. CCS Concepts •Computing methodologies → Animation; Shape modeling;
We introduce here a pipeline for simplifying digital 3D shapes with the aim of fabricating them using 2D polygonal flat parts. Our method generates shapes that, once unfolded, can be fabricated with CNC milling machines using special tools called V-Grooves. These tools make V-shaped furrows at given angles depending on the shape of the used tool. Milling the edges of each flat facet simplifies the manual assembly that consists only in folding the facets at the desired angle between the adjacent facets. Our method generates simplified shapes where every dihedral angle between adjacent facets belongs to a restricted set, thus making the assembly process quicker and more straightforward. Firstly, our method automatically computes a simplification of the model, iterating local changes on a triangle mesh generated by applying the Marching Cubes algorithm on the original mesh. The user performs a second manual simplification using a tool that removes spurious facets. Finally, we use a simple unfolding algorithm which flattens the polygonal facets onto the 2D plane, so that a CNC milling machine can fabricate it with a sheet of rigid material. CCS Concepts •Computing methodologies → Mesh models; Shape analysis; Shape modeling;
The techniques for rendering woven cloth employed in a production environment often neglect many of the structural features of the fabric, as well as light-scattering processes that occur in the yarn. Research in this area has progressed, and new promising methods have recently been proposed; however, many of these are not applied in practice due to their inherent complexities. In this paper, we develop and implement a shader for woven cloth that fulfills some of the needs of a production environment using an existing model for simulating the interaction with light. The shader delivers highly realistic results that are comparable, and in some cases superior, to current methods used in a real production environment. We enriched and validated the proposed framework by using direct feedback from a large company that produces images of furniture using computer graphics. The results demonstrate that our shader accurately simulates the appearance of certain types of woven cloth, showing reflections that are not present in other methods in current use. Our shader is easy to integrate in existing pipelines, flexible because it provides the artist with enough parameters to recreate many different types of fabric, and generic for the domain of woven cloth because it is able to accept as input widely used WIF files, which describe weave patterns as well as yarn specific parameters.
The reconstruction of the physical environment using a depth sensor involves data-intensive computations which are difficult to implement on mobile systems (e.g., tracking and aligning the position of the sensor with the depth maps). In this paper, we present two practical experimental setups for scanning and reconstructing real objects employing low-price, off-the-shelf embedded components and open-source libraries. As a test case, we scan and reconstruct a 23 m high statue using an octocopter without employing external hardware.
In this work, after a careful examination of the most common errors and flaws which typically occur in meshes produced by 3D scanning processes, we propose a set of fixing tools which solve effectively several important mesh defects while preserving the original data. The proposed tools are then organized and activated in the RameshCleaner pipeline allowing the user to take advantage of a semi-automated fixing solution, optimized for speed and efficiency, as well as of the possibility to selectively activate individual tools. The comparison, over a set of representative scanned models, with free and commercial semi-automated fixing solutions gives a significant evidence of the defect abatement and computational speed characteristics of the proposed system.
In the digital age of medicine, patient-specific 3D anatomical reconstructions are becoming increasingly relevant in several applications, starting from bio-mechanical simulation, virtual surgery, implant design to computer-assisted diagnosis. While problems related to imaging and 3D reconstruction have been largely resolved by the advancement in technologies, tools for extracting, coding, sharing and retrieving the semantic content of the patient-specific 3D models are still far from being satisfactory. In this context, we propose SemAnatomy3D framework that aims to bridge the semantic gap between patient-specific 3D geometry and formalized domain knowledge for making the semantics more usable for the definition of patient-specific atlas of anatomy. The purpose of this paper is to describe primary components of the framework. We specialized our framework for the carpal region, but, in principle, it can support similar tasks for other anatomical districts.
Thanks to modern high-resolution acquisition techniques, 3D digital representations of real objects are easily made of millions, or even billions, of elements. Processing and analysing such large datasets is often a non trivial task, due to specific software and hardware requirements. Our system allows to process large triangle meshes by exploiting nothing more than a standard Web browser. A graphical interface allows to select among available algorithms and to stack them into complex pipelines, while a central engine manages the overall execution by exploiting both hardware and software provided by a distributed network of servers. As an additional feature, our system allows to store work ows and to make them publicly available. A semantic-driven search mechanism is provided to allow the retrieval of specific work ows. Besides the technological contribution, an innovative mesh transfer protocol avoids possible bottlenecks during the transmission of data across scattered servers. Also, distributed parallel processing is enabled thanks to an innovative divide and conquer approach. A simplification algorithm based on this paradigm proves that the overhead due to data transmission is negligible.
Curve-skeletons are well known shape descriptors, able to encode topological and structural information of a shape. The range of applications in which they are used comprises, to name a few, computer animation, shape matching, modelling and remeshing. Different tools for automatically extracting the curve-skeleton for a given input mesh are currently available, as well as inverse skeletonization tools, where a user-defined skeleton is taken as input in order to build a mesh that reflects the encoded structure. Although their use is broad, an automatically extracted curve-skeleton is usually not well-suited for the next pipeline step in which they will be used. We present a tool for creating, editing and repairing curve-skeletons whose aim is to allow users to obtain, within minutes, curve-skeletons that are tailored for their specific task.
In historical documentaries, video material often is not available. For this reason they are mainly made by using static material such as old photographs. To make this material more endearing and dynamic an effect known as “Ken Burns Effect” can be applied to the static images. It consists in a mix of panning and zooming effect applied to different objects which belong to an image. Hence, considerable user experience with photo and video editing software is required to successfully separate the objects from the background and to animate them to produce a high quality result. In this paper, we present an algorithm to apply Ken Burns effect with a minimal user interaction. The proposed solution exploits Statistical Region Merging segmentation algorithm to support the user in the process of separation of the objects from the background. Moreover, Inpainting algorithms are employed to fill the empty regions which becomes visible when an object is moved from its original position. Finally a random video can be produced from different “animated” images.
This paper presents a novel method for diffuse texture extraction from a set of multiview images. We address the problem of specularities removal by pixel value minimization across multiple automatically aligned input images. Our method is based on the fact that the presence of specular reflection only increases the captured pixel value. Moreover, we propose an algorithm for estimation of material region in the image by optimization on the GPU. Previous methods for diffuse component separation from multiple images require a complex hardware setup. In contrast to that, our method is highly usable because only a mobile phone is needed to reconstruct diffuse texture in an environment with arbitrary lighting. Moreover, our method is fully automatic and besides capturing of images from multiple viewpoints it does not require any user intervention. Many fields can benefit from our method, particularly material reconstruction, image processing, and digital content creation.
With ever increasing ray traversal and hierarchy construction performance the application of ray tracing to problems often tackled by rasterization-based algorithms is becoming a viable alternative. This is especially desirable as the ground truth for these algorithms is often determined by using ray tracing and thus directly applying it is the simplest way to generate images satisfying the reference. In this paper we propose a very efficient pre-process to speed up the construction and traversal of sub-optimal, but fast-to-build hierarchies used for interactive ray tracing and show how it can be applied to shadow rays in a hybrid environment, where ray tracing is used to sample area lights for scene positions found and shaded via rasterization.
This study aims to generate synthetic and realistic retinal fundus colour images, similar in characteristics to a given dataset, as well as the values of all morphological parameters. A representative task could be, for example, the synthesis of a retinal image with the corresponding vessel tree and optic nerve head binary map, measurement of vessel width in any position, fovea localisation and so on. The presented paper mainly focuses on the generation of non-vascular regions (i.e. retinal background, fovea and optic disc) and it is complemented by a parallel study on the generation of structure and texture of the vessel network. To synthesise convincing retinal backgrounds and foveae, a patchbased algorithm has been developed; model-based texture synthesis techniques have also been implemented for the generation of realistic optic discs. The validity of our synthetic retinal images has been demonstrated by visual inspection and quantitative experiments.
Chroma Key is a special-effects technique widely used by television and motion picture industries for image composition. This technique allows users to replace sections identified by a chosen colour in a multimedia stream (like a video or a photo) with another image or video stream. In this paper, we describe an easy-to-implement technique for the creation of an Android based application for mobile devices (like smartphones and tablets) that applies Chroma Key-based effects to the video stream coming from the device camera. We discuss the algorithm used to achieve the Chroma Key effect focusing on the computational performance and on the quality of its final result. Using a picture selected from the device gallery, this application makes possible the replacement of video stream background areas characterized by a chroma value with the chosen picture.
Splat-based models are a good representation because of its absense of topology, making complex modeling operations easier, but keeping the same approximation ratio from triangular meshes. However corners cannot be properly represented by splats without clipping them. We present a new method for clipping splats in models with sharp features. Each splat is an ellipse equipped with a few parameters that allow to define how the ellipse can be clipped against a bidimensional rational Bézier curve and thus it can be used for all those surfaces that show a large number of edge features and different sampling rate around them. The simple and uniform data used to define the clipping curve makes easy the implementation in GPU. We designed and implemented an automatic computation of the clipping curves and a pipeline for sampling a generic surface with splats and render it. In this paper we show how this technique outperforms the previous clipping techniques in precision for objects such as mechanical parts and CAD- like models keeping the rendering speed.
Objects made of different media, paintings, marbles, clay and wooden objects, textiles etc., form the historical collections of most of the middle to medium sized Museums in Italy. This variety poses difficult challenges to these institutions when they face the digitalization of part of their patrimony. This paper provides a report of an ongoing inter-disciplinary experimental program for a digitalization effort to be carried out by one of such institution. Through the discussion of the digitalization of different objects obtained with the use and integration of different techniques we illustrate some of the lessons learned in transferring to the final intended users the graphical tools and the know-how previously acquired in a research laboratory.
Car models typically consist of highly specular surfaces including sharp angles. Renderings of such models contain very fine, sharp lighting features, that both make Level-of-Detail switches well visible and result in strong aliasing artifacts. In this paper we address both issues. As Level-of-Detail approach, we apply on-the-fly vertex clustering and introduce a texture coordinate correction to remove popping artifacts, that become visible during mesh simplification. By replacing vertex normals with texture normals, we can provide stable lighting features, even if the underlying mesh changes. To prevent aliasing effects on specular highlights, we then apply a variant of LEAN mapping (linear efficient antialiased normal mapping). We observe that LEAN mapping cannot be applied directly, because in our scenario we need to filter object space normals, as we have no presupposed tangent-space availeble. We therefore create a per-texel tangent space from an object space MIP normal, thus retaining the benefits of a 2D distribution without a preexisting tangent space. Both approaches in combination, allow us to render highly reflective, detailed models with continuous level of detail and anti-aliased lighting, at the price of moderately increased memory consumption and render time.
