![]() ![]() ![]() Using this constrained acquisition scenario and our deformable mesh framework, it is possible to reconstruct high quality 3D models. By taking multiple image-light pairs around an object, multi-view Helmholtz stereo can be performed. Helmholtz reciprocity can also be applied to reconstruct 3D shapes of objects of any arbitrary reflectance properties. Segmentation for instance can be used to segment surface regions sharing similar appearance or reflectance. Then, we propose to exploit different additional information to constraint the problem in the non-Lambertian case, where the appearance of the scene depends on the view-point direction. The same framework can then be equally used to perform multi-view stereo, multi-view shape from shading or multi-view photometric stereo. We particularly focus on models and energy functionals that depend on visibility and photometry. A particular attention is addressed to the computation of the discrete gradient flow, which leads to coherent vertices displacements. Using generative models, we formulate the problem as an energy minimization method that leads to the non-linear surface optimization of a deformable mesh. We first formulate multi-view shape reconstruction as an inverse rendering problem. In this thesis, we address several geometric and photometric aspects to 3D surface reconstruction from multi-view calibrated images. Understanding, analyzing and modeling the 3D world from 2D pictures and videos is probably one of the most exciting and challenging problem of computer vision. Results are illustrated on real data from a system composed of six projectors and six cameras that was actually built. In the experiments, we show that we can successfully reconstruct dense entire shapes of moving objects. In addition, we also propose efficient noise reduction and mesh generation algorithm which are necessary for practical applications. ![]() To achieve this, we mainly propose two additional steps one is checking the consistency between the multiple cameras and projectors, and the other is an algorithm for light sectioning based on a plane parameter optimization. In this paper, we extend the technique to capture a dense entire shape of a moving object with accuracy and high video frame rate. Like previous approaches, a static and simple pattern is used to avoid interferences of multiple patterns projected on the same object. This is performed using a multiple projectors and cameras system, that allows to recover the entire shape of the object within a single scan at each frame. In this paper, we propose to acquire the entire 3D shape of a dynamic scene. The suffix at the end of the model number is omitted.Active vision systems are usually limited to either partial or static scene reconstructions. Product availability may vary by country or region. *6 Requires Optional AJ-WM50 Wireless Module. Estimated time until light output declines to 50 % varies depending on environment. IEC62087: 2008 Broadcast contents, NORMAL Mode, Dynamic Contrast, under conditions with 30 ☌ (86 ☏), 700 m (2,297 ft) above sea level, and 0.15 mg/m 3 of particulate matter. *4 Around this time, light output will have decreased by approximately 50 %. Applicable terminals: DIGITAL LINK terminal/HDMI terminal. A signal with different resolution is converted to the number of display dots. *2 PT-VMZ40 does not feature a DIGITAL LINK terminal. *1 For LCD Laser projectors in the 5,000-lumens-class or higher (PT-VMZ40 excluded) as of June 2019.
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