4,076 research outputs found

    Towards sketch-based exploration of terrain : a feasibility study

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    CISRG discussion paper ; 1

    Beyond factual to formulated silhouettes

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    When sketching terrain, a view-dependent framework of silhouette-related cues is required. This framework is prominent in manual sketches and is especially important in small-scale depictions viewed obliquely from above. Occluding contours, namely the lines delineating depth discontinuities in the projected surface, are insufficient for forming this framework. The role which the occluding contour, or Factual Silhouette, plays in structuring the sketch becomes increasingly minimal as more of the terrain becomes visible, as the viewpoint is raised.The aim of this research is to extend the set of occluding contours to encompass situations that are perceived as causing an occlusion and would therefore be sketched in a similar manner. These locations, termed Formulated Silhouettes supplement the set of occluding contours and provide a successful structuring framework. The proposed method processes visible areas of terrain, which are turning away from view, to extract a classified, vector-based description for a given view of a Digital Elevation Model. Background approaches to silhouette rendering are reviewed and the specific contributions of this thesis are discussed.The method is tested using case studies composed of terrain of varying scale and character and two application studies demonstrate how silhouettes can be used to enhance existing terrain visualization techniques, both abstract and realistic. In addition, consultation with cartographic designers provides external verification of the research. The thesis concludes by noting how silhouette contours relate to perceived entities rather than actual occlusions

    Feature-rich distance-based terrain synthesis

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    This thesis describes a novel terrain synthesis method based on distances in a weighted graph. The method begins with a regular lattice with arbitrary edge weights; heights are determined by path cost from a set of generator nodes. The shapes of individual terrain features, such as mountains, hills, and craters, are specified by a monotonically decreasing profile describing the cross-sectional shape of a feature, while the locations of features in the terrain are specified by placing the generators. Pathing places ridges whose initial location have a dendritic shape. The method is robust and easy to control, making it possible to create pareidolia effects. It can produce a wide range of realistic synthetic terrains such as mountain ranges, craters, faults, cinder cones, and hills. The algorithm incorporates random graph edge weights, permits the inclusion of multiple topography profiles, and allows precise control over placement of terrain features and their heights. These properties all allow the artist to create highly heterogeneous terrains that compare quite favorably to existing methods

    Sketching-based Skeleton Extraction

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    Articulated character animation can be performed by manually creating and rigging a skeleton into an unfolded 3D mesh model. Such tasks are not trivial, as they require a substantial amount of training and practice. Although methods have been proposed to help automatic extraction of skeleton structure, they may not guarantee that the resulting skeleton can help to produce animations according to user manipulation. We present a sketching-based skeleton extraction method to create a user desired skeleton structure which is used in 3D model animation. This method takes user sketching as an input, and based on the mesh segmentation result of a 3D mesh model, generates a skeleton for articulated character animation. In our system, we assume that a user will properly sketch bones by roughly following the mesh model structure. The user is expected to sketch independently on different regions of a mesh model for creating separate bones. For each sketched stroke, we project it into the mesh model so that it becomes the medial axis of its corresponding mesh model region from the current viewer perspective. We call this projected stroke a “sketched bone”. After pre-processing user sketched bones, we cluster them into groups. This process is critical as user sketching can be done from any orientation of a mesh model. To specify the topology feature for different mesh parts, a user can sketch strokes from different orientations of a mesh model, as there may be duplicate strokes from different orientations for the same mesh part. We need a clustering process to merge similar sketched bones into one bone, which we call a “reference bone”. The clustering process is based on three criteria: orientation, overlapping and locality. Given the reference bones as the input, we adopt a mesh segmentation process to assist our skeleton extraction method. To be specific, we apply the reference bones and the seed triangles to segment the input mesh model into meaningful segments using a multiple-region growing mechanism. The seed triangles, which are collected from the reference bones, are used as the initial seeds in the mesh segmentation process. We have designed a new segmentation metric [1] to form a better segmentation criterion. Then we compute the Level Set Diagrams (LSDs) on each mesh part to extract bones and joints. To construct the final skeleton, we connect bones extracted from all mesh parts together into a single structure. There are three major steps involved: optimizing and smoothing bones, generating joints and forming the skeleton structure. After constructing the skeleton model, we have proposed a new method, which utilizes the Linear Blend Skinning (LBS) technique and the Laplacian mesh deformation technique together to perform skeleton-driven animation. Traditional LBS techniques may have self-intersection problem in regions around segmentation boundaries. Laplacian mesh deformation can preserve the local surface details, which can eliminate the self-intersection problem. In this case, we make use of LBS result as the positional constraint to perform a Laplacian mesh deformation. By using the Laplacian mesh deformation method, we maintain the surface details in segmentation boundary regions. This thesis outlines a novel approach to construct a 3D skeleton model interactively, which can also be used in 3D animation and 3D model matching area. The work is motivated by the observation that either most of the existing automatic skeleton extraction methods lack well-positioned joints specification or the manually generated methods require too much professional training to create a good skeleton structure. We dedicate a novel approach to create 3D model skeleton based on user sketching which specifies articulated skeleton with joints. The experimental results show that our method can produce better skeletons in terms of joint positions and topological structure

    Drawing, Handwriting Processing Analysis: New Advances and Challenges

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    International audienceDrawing and handwriting are communicational skills that are fundamental in geopolitical, ideological and technological evolutions of all time. drawingand handwriting are still useful in defining innovative applications in numerous fields. In this regard, researchers have to solve new problems like those related to the manner in which drawing and handwriting become an efficient way to command various connected objects; or to validate graphomotor skills as evident and objective sources of data useful in the study of human beings, their capabilities and their limits from birth to decline

    Cross-Modal Hierarchical Modelling for Fine-Grained Sketch Based Image Retrieval

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    Sketch as an image search query is an ideal alternative to text in capturing the fine-grained visual details. Prior successes on fine-grained sketch-based image retrieval (FG-SBIR) have demonstrated the importance of tackling the unique traits of sketches as opposed to photos, e.g., temporal vs. static, strokes vs. pixels, and abstract vs. pixel-perfect. In this paper, we study a further trait of sketches that has been overlooked to date, that is, they are hierarchical in terms of the levels of detail -- a person typically sketches up to various extents of detail to depict an object. This hierarchical structure is often visually distinct. In this paper, we design a novel network that is capable of cultivating sketch-specific hierarchies and exploiting them to match sketch with photo at corresponding hierarchical levels. In particular, features from a sketch and a photo are enriched using cross-modal co-attention, coupled with hierarchical node fusion at every level to form a better embedding space to conduct retrieval. Experiments on common benchmarks show our method to outperform state-of-the-arts by a significant margin.Comment: Accepted for ORAL presentation in BMVC 202

    New methods, techniques and applications for sketch recognition

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    2012-2013The use of diagrams is common in various disciplines. Typical examples include maps, line graphs, bar charts, engineering blueprints, architects’ sketches, hand drawn schematics, etc.. In general, diagrams can be created either by using pen and paper, or by using specific computer programs. These programs provide functions to facilitate the creation of the diagram, such as copy-and-paste, but the classic WIMP interfaces they use are unnatural when compared to pen and paper. Indeed, it is not rare that a designer prefers to use pen and paper at the beginning of the design, and then transfer the diagram to the computer later. To avoid this double step, a solution is to allow users to sketch directly on the computer. This requires both specific hardware and sketch recognition based software. As regards hardware, many pen/touch based devices such as tablets, smartphones, interactive boards and tables, etc. are available today, also at reasonable costs. Sketch recognition is needed when the sketch must be processed and not considered as a simple image and it is crucial to the success of this new modality of interaction. It is a difficult problem due to the inherent imprecision and ambiguity of a freehand drawing and to the many domains of applications. The aim of this thesis is to propose new methods and applications regarding the sketch recognition. The presentation of the results is divided into several contributions, facing problems such as corner detection, sketched symbol recognition and autocompletion, graphical context detection, sketched Euler diagram interpretation. The first contribution regards the problem of detecting the corners present in a stroke. Corner detection is often performed during preprocessing to segment a stroke in single simple geometric primitives such as lines or curves. The corner recognizer proposed in this thesis, RankFrag, is inspired by the method proposed by Ouyang and Davis in 2011 and improves the accuracy percentages compared to other methods recently proposed in the literature. The second contribution is a new method to recognize multi-stroke hand drawn symbols, which is invariant with respect to scaling and supports symbol recognition independently from the number and order of strokes. The method is an adaptation of the algorithm proposed by Belongie et al. in 2002 to the case of sketched images. This is achieved by using stroke related information. The method has been evaluated on a set of more than 100 symbols from the Military Course of Action domain and the results show that the new recognizer outperforms the original one. The third contribution is a new method for recognizing multi-stroke partially hand drawn symbols which is invariant with respect to scale, and supports symbol recognition independently from the number and order of strokes. The recognition technique is based on subgraph isomorphism and exploits a novel spatial descriptor, based on polar histograms, to represent relations between two stroke primitives. The tests show that the approach gives a satisfactory recognition rate with partially drawn symbols, also with a very low level of drawing completion, and outperforms the existing approaches proposed in the literature. Furthermore, as an application, a system presenting a user interface to draw symbols and implementing the proposed autocompletion approach has been developed. Moreover a user study aimed at evaluating the human performance in hand drawn symbol autocompletion has been presented. Using the set of symbols from the Military Course of Action domain, the user study evaluates the conditions under which the users are willing to exploit the autocompletion functionality and those under which they can use it efficiently. The results show that the autocompletion functionality can be used in a profitable way, with a drawing time saving of about 18%. The fourth contribution regards the detection of the graphical context of hand drawn symbols, and in particular, the development of an approach for identifying attachment areas on sketched symbols. In the field of syntactic recognition of hand drawn visual languages, the recognition of the relations among graphical symbols is one of the first important tasks to be accomplished and is usually reduced to recognize the attachment areas of each symbol and the relations among them. The approach is independent from the method used to recognize symbols and assumes that the symbol has already been recognized. The approach is evaluated through a user study aimed at comparing the attachment areas detected by the system to those devised by the users. The results show that the system can identify attachment areas with a reasonable accuracy. The last contribution is EulerSketch, an interactive system for the sketching and interpretation of Euler diagrams (EDs). The interpretation of a hand drawn ED produces two types of text encodings of the ED topology called static code and ordered Gauss paragraph (OGP) code, and a further encoding of its regions. Given the topology of an ED expressed through static or OGP code, EulerSketch automatically generates a new topologically equivalent ED in its graphical representation. [edited by author]XII n.s
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