Adaptive Scanning for Online 3D Model Acquisition

Koninckx, Thomas; Jaeggli, Tobias; Gool, Luc Van

doi:10.1109/cvpr.2004.295

Cited by 6 publications

(3 citation statements)

References 17 publications

(17 reference statements)

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“…For interactive applications, real-time, motion-insensitive range scanners are necessary to provide input data. Such systems have been proposed based on laser scanners [20,6,42], time-of-flight cameras [31,24,8], passive stereo [11], and structured light [36,49,29,45,27]. Structured-light systems have the advantage that they provide a dense 2D depth map per frame with higher accuracy than current time-of-flight and stereo cameras.…”

Section: Related Workmentioning

confidence: 99%

Online loop closure for real-time interactive 3D scanning

Weise

Wismer

Leibe

et al. 2011

Computer Vision and Image Understanding

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We present a real-time interactive 3D scanning system that allows users to scan complete object geometry by turning the object around in front of a real-time 3D range scanner. The incoming 3D surface patches are registered and integrated into an online 3D point cloud. In contrast to previous systems the online reconstructed 3D model also serves as final result. Registration error accumulation which leads to the well-known loop closure problem is addressed already during the scanning session by distorting the object as rigidly as possible. Scanning errors are removed by explicitly handling outliers based on visibility constraints. Thus, no additional post-processing is required which otherwise might lead to artifacts in the model reconstruction. Both geometry and texture are used for registration which allows for a wide range of objects with different geometric and photometric properties to be scanned. We show the results of our modeling approach on several difficult real-world objects. Qualitative and quantitative results are given for both synthetic and real data demonstrating the importance of online loop closure and outlier handling for model reconstruction. We show that our real-time scanning system has comparable accuracy to offline methods with the additional benefit of immediate feedback and results.

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Section: Related Workmentioning

confidence: 99%

Online loop closure for real-time interactive 3D scanning

Weise

Wismer

Leibe

et al. 2011

Computer Vision and Image Understanding

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“…Koninckx et al proposed a technique allowing dense shape reconstruction based on a single image using a simple pattern, i.e. a set of stripes [9,10] stripes. Their method depends on relative numbering of the dense patterns, which assumes local smoothness of the surface and may be disturbed by shape discontinuities and line detection failures.…”

Section: Related Workmentioning

confidence: 99%

3D Scanning Method for Fast Motion using Single Grid Pattern with Coarse-to-fine Technique

Furukawa

Kawasaki

Sagawa

et al. 2008

Procedings of the British Machine Vision Conference 2008

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An active 3D scanning method that can capture a fast motion is strongly required in wide areas. Since most commercial products using a laser projector basically reconstruct the shape with a point or a line for each scan, a fast motion cannot be captured in principle. In addition, an extended method using a structured light can drastically reduce the number of projecting patterns, however, they still require several patterns and a fast motion cannot be captured. One solution for the purpose is to use a single pattern (one shot scan). Although, one shot scanning methods have been intensively studied, they often have stability problems and their result tend to have low resolution. In this paper, we develop a new system which achieves dense and robust 3D measurement from a single grid pattern. A 3D reconstruction can be achieved by identifying grid patterns using coplanarity constraints. We also propose a coarse-to-fine method to increase the density of the shape with a single pattern.

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“…They however still rely on offline computations. On-line systems, that compute and visualise 3D reconstructions on-the-fly 5,6 open a wide area of new possibilities. Next to the obvious advantages such as immediate visual validation of the data, such systems potentially can adapt themselves to characteristics of the scene in order to obtain optimal results.…”

Section: Previous Workmentioning

confidence: 99%

Model-based sparse 3D reconstruction for online body tracking

2005

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In this paper a new approach to 3D human body tracking is proposed. A sparse 3D reconstruction of the subject to be tracked is made using a structured light system consisting of a precalibrated LCD projector and a camera. At a number of points-of-interest, easily detectable features are projected. The resulting sparse 3D reconstruction is used to estimate the body pose of the tracked person. This new estimate of the body pose is then fed back to the structured light system and allows to adapt the projected patterns, i.e. decide where to project features. Given the observations, a physical simulation is used to estimate the body pose by attaching forces to the limbs of the body model. The sparse 3D observations are augmented by denser silhouette information, in order to make the tracking more robust. Experiments demonstrate the feasibility of the proposed approach and show that the high speeds that are required due to the closed feedback loop can be achieved.

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Adaptive Scanning for Online 3D Model Acquisition

Cited by 6 publications

References 17 publications

Online loop closure for real-time interactive 3D scanning

Online loop closure for real-time interactive 3D scanning

3D Scanning Method for Fast Motion using Single Grid Pattern with Coarse-to-fine Technique

Model-based sparse 3D reconstruction for online body tracking

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