110,495 research outputs found

    Shape from X: Psychophysics and Computation

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    This chapter contains sections titled: The Many Routes to Shape, The Need for Integration, Shape From Stereo and Shading (Local Measurements) 1 , Shape from Shading and Texture (Global Measurements), Shape from Disparate Shading (Intensity-Based Stereo), Shape from Highlights 2 , Integration of Depth Modules, A Bayesian Framework for Cue Integration 3 , Final Remarks, Acknowledgments, Appendices, Reference

    Depth Recovery of Complex Surfaces from Texture-less Pairs of Stereo Images

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    In this paper, a novel framework is presented to recover the 3D shape information of a complex surface using its texture-less stereo images. First a linear and generalized Lambertian model is proposed to obtain the depth information by shape from shading (SfS) using an image from stereo pair. Then this depth data is corrected by integrating scale invariant features (SIFT) indexes. These SIFT indexes are defined by means of disparity between the matching invariant features in rectified stereo images. The integration process is based on correcting the 3D visible surfaces obtained from SfS using these SIFT indexes. The SIFT indexes based improvement of depth values which are obtained from generalized Lambertian reflectance model is performed by a feed-forward neural network. The experiments are performed to demonstrate the usability and accuracy of the proposed framework

    Creating Simplified 3D Models with High Quality Textures

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    This paper presents an extension to the KinectFusion algorithm which allows creating simplified 3D models with high quality RGB textures. This is achieved through (i) creating model textures using images from an HD RGB camera that is calibrated with Kinect depth camera, (ii) using a modified scheme to update model textures in an asymmetrical colour volume that contains a higher number of voxels than that of the geometry volume, (iii) simplifying dense polygon mesh model using quadric-based mesh decimation algorithm, and (iv) creating and mapping 2D textures to every polygon in the output 3D model. The proposed method is implemented in real-time by means of GPU parallel processing. Visualization via ray casting of both geometry and colour volumes provides users with a real-time feedback of the currently scanned 3D model. Experimental results show that the proposed method is capable of keeping the model texture quality even for a heavily decimated model and that, when reconstructing small objects, photorealistic RGB textures can still be reconstructed.Comment: 2015 International Conference on Digital Image Computing: Techniques and Applications (DICTA), Page 1 -

    Real-time High Resolution Fusion of Depth Maps on GPU

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    A system for live high quality surface reconstruction using a single moving depth camera on a commodity hardware is presented. High accuracy and real-time frame rate is achieved by utilizing graphics hardware computing capabilities via OpenCL and by using sparse data structure for volumetric surface representation. Depth sensor pose is estimated by combining serial texture registration algorithm with iterative closest points algorithm (ICP) aligning obtained depth map to the estimated scene model. Aligned surface is then fused into the scene. Kalman filter is used to improve fusion quality. Truncated signed distance function (TSDF) stored as block-based sparse buffer is used to represent surface. Use of sparse data structure greatly increases accuracy of scanned surfaces and maximum scanning area. Traditional GPU implementation of volumetric rendering and fusion algorithms were modified to exploit sparsity to achieve desired performance. Incorporation of texture registration for sensor pose estimation and Kalman filter for measurement integration improved accuracy and robustness of scanning process

    Light Field Blind Motion Deblurring

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    We study the problem of deblurring light fields of general 3D scenes captured under 3D camera motion and present both theoretical and practical contributions. By analyzing the motion-blurred light field in the primal and Fourier domains, we develop intuition into the effects of camera motion on the light field, show the advantages of capturing a 4D light field instead of a conventional 2D image for motion deblurring, and derive simple methods of motion deblurring in certain cases. We then present an algorithm to blindly deblur light fields of general scenes without any estimation of scene geometry, and demonstrate that we can recover both the sharp light field and the 3D camera motion path of real and synthetically-blurred light fields.Comment: To be presented at CVPR 201

    Integration of texture and disparity cues to surface slant in dorsal visual cortex.

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    Reliable estimation of three-dimensional (3D) surface orientation is critical for recognizing and interacting with complex 3D objects in our environment. Human observers maximize the reliability of their estimates of surface slant by integrating multiple depth cues. Texture and binocular disparity are two such cues, but they are qualitatively very different. Existing evidence suggests that representations of surface tilt from each of these cues coincide at the single-neuron level in higher cortical areas. However, the cortical circuits responsible for 1) integration of such qualitatively distinct cues and 2) encoding the slant component of surface orientation have not been assessed. We tested for cortical responses related to slanted plane stimuli that were defined independently by texture, disparity, and combinations of these two cues. We analyzed the discriminability of functional MRI responses to two slant angles using multivariate pattern classification. Responses in visual area V3B/KO to stimuli containing congruent cues were more discriminable than those elicited by single cues, in line with predictions based on the fusion of slant estimates from component cues. This improvement was specific to congruent combinations of cues: incongruent cues yielded lower decoding accuracies, which suggests the robust use of individual cues in cases of large cue conflicts. These data suggest that area V3B/KO is intricately involved in the integration of qualitatively dissimilar depth cues

    Integrated geotechnical and geophysical investigation of a proposed construction site at Mowe, Southwestern Nigeria

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    The subsurface of a proposed site for building development in Mowe, Nigeria, using Standard Penetration Test (SPT), Cone Penetrometer Test (CPT) and Horizontal Electrical Profiling (HEP), was investigated with the aim of evaluating the suitability of the strata for foundation materials. Four SPT and CPT were conducted using 2.5 tonnes hammer. HEP utilizing Wenner array were performed with inter-electrode spacing of 10 – 60 m along four traverses coincident with each of the SPT and CPT. The HEP data were processed using DIPRO software and textural filtering of the resulting resistivity sections was implemented to enable delineation of hidden layers. Sandy lateritic clay, silty lateritic clay, clay, clayey sand and sand horizons were delineated. The SPT “N” value defined very soft to soft sandy lateritic (<4), stiff silty lateritic clay (7 – 12), very stiff silty clay (12 - 15), clayey sand (15- 20) and sand (27 – 37). Sandy lateritic clay (5-40 kg/cm2) and silty lateritic clay (25 - 65 kg/cm2) were defined from the CPT response. Sandy lateritic clay (220-750 Ωm), clay (< 50 Ωm) and sand (415-5359 Ωm) were delineated from the resistivity sections with two thin layers of silty lateritic clay and clayey sand defined in the texturally filtered resistivity sections. Incompetent clayey materials that are unsuitable for the foundation of the proposed structure underlain the study area to a depth of about 18m. Deep foundation involving piling through the incompetent shallow layers to the competent sand at 20 m depth was recommended

    Rendering techniques for multimodal data

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    Many different direct volume rendering methods have been developed to visualize 3D scalar fields on uniform rectilinear grids. However, little work has been done on rendering simultaneously various properties of the same 3D region measured with different registration devices or at different instants of time. The demand for this type of visualization is rapidly increasing in scientific applications such as medicine in which the visual integration of multiple modalities allows a better comprehension of the anatomy and a perception of its relationships with activity. This paper presents different strategies of Direct Multimodal Volume Rendering (DMVR). It is restricted to voxel models with a known 3D rigid alignment transformation. The paper evaluates at which steps of the render-ing pipeline must the data fusion be realized in order to accomplish the desired visual integration and to provide fast re-renders when some fusion parameters are modified. In addition, it analyzes how existing monomodal visualization al-gorithms can be extended to multiple datasets and it compares their efficiency and their computational cost.Postprint (published version
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