3D Modeling of Outdoor Environments by Integrating Omnidirectional Range and Color Images

Asai, Toshihiro; Kanbara, Masayuki; Yokoya, Naokazu

doi:10.1109/3dim.2005.3

Cited by 21 publications

(16 citation statements)

References 17 publications

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“…Such direct georeferencing is often applied in mobile laser scanner applications (e.g. Asai et al, 2005). Due to the uncertainty of the additional sensors, the resulting registration is often rather coarse.…”

Section: Related Workmentioning

confidence: 99%

Automatic Registration of Terrestrial Laser Scanner Point Clouds Using Natural Planar Surfaces

Theiler

Schindler

2012

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Terrestrial laser scanners have become a standard piece of surveying equipment, used in diverse fields like geomatics, manufacturing and medicine. However, the processing of today's large point clouds is time-consuming, cumbersome and not automated enough. A basic step of post-processing is the registration of scans from different viewpoints. At present this is still done using artificial targets or tie points, mostly by manual clicking. The aim of this registration step is a coarse alignment, which can then be improved with the existing algorithm for fine registration. The focus of this paper is to provide such a coarse registration in a fully automatic fashion, and without placing any target objects in the scene. The basic idea is to use virtual tie points generated by intersecting planar surfaces in the scene. Such planes are detected in the data with RANSAC and optimally fitted using least squares estimation. Due to the huge amount of recorded points, planes can be determined very accurately, resulting in well-defined tie points. Given two sets of potential tie points recovered in two different scans, registration is performed by searching for the assignment which preserves the geometric configuration of the largest possible subset of all tie points. Since exhaustive search over all possible assignments is intractable even for moderate numbers of points, the search is guided by matching individual pairs of tie points with the help of a novel descriptor based on the properties of a point's parent planes. Experiments show that the proposed method is able to successfully coarse register TLS point clouds without the need for artificial targets.

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Section: Related Workmentioning

confidence: 99%

Automatic Registration of Terrestrial Laser Scanner Point Clouds Using Natural Planar Surfaces

Theiler

Schindler

2012

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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“…LIDAR is one of the most popular depth ranging techniques, which measures the range by the time delay between transmission of a pulse and detection of the reflected signal (Lemmens, 2007). Asai et al (2005) developed a 3D reconstruction system for outdoor areas using a laser rangefinder and an omnidirectional multi-camera system which can capture a wide-angle high-resolution image. They captured range and colour images at 68 points in their university campus and merged them into a common 3D space.…”

Section: Environment Modellingmentioning

confidence: 99%

“…Point Grey developed an omnidirectional multicamera system, the Ladybug 2 , which consists of six XGA color CCDs to overcome the resolution problem. Asai et al (2005) used this Ladybug for outdoor environment modelling by combining it with a range sensor. Google also developed their own omnidirectional multicamera system to reconstruct and render street models (Anguelov et al, 2010).…”

Section: Reconstruction From Spherical Imagesmentioning

confidence: 99%

3D Scene Reconstruction from Multiple Spherical Stereo Pairs

Kim

Hilton

2013

Int J Comput Vis

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We propose a 3D environment modelling method using multiple pairs of high-resolution spherical images. Spherical images of a scene are captured using a rotating line scan camera. Reconstruction is based on stereo image pairs with a vertical displacement between camera views. A 3D mesh model for each pair of spherical images is reconstructed by stereo matching. For accurate surface reconstruction, we propose a PDE-based disparity estimation method which produces continuous depth fields with sharp depth discontinuities even in occluded and highly textured regions. A full environment model is constructed by fusion of partial reconstruction from spherical stereo pairs at multiple widely spaced locations. To avoid camera calibration steps for all camera locations, we calculate 3D rigid transforms between capture points using feature matching and register all meshes into a unified coordinate system. Finally a complete 3D model of the environment is generated by selecting the most reliable observations among overlapped surface measurements considering surface visibility, orientation and distance from the camera. We analyse the characteristics and behaviour of errors for spherical stereo imaging. Performance of the proposed algorithm is evaluated against ground-truth from the Middlebury stereo test bed and LIDAR scans. Results are also compared with conventional structure-frommotion algorithms. The final composite model is rendered from a wide range of viewpoints with high quality textures.

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“…We have proposed a plane based ICP algorithm for range data acquired in outdoor environments 10 . The registration method applies to the system because the method 10 can stably register range data in outdoor environments.…”

Section: Registration Of Range Datamentioning

confidence: 99%

Data acquiring support system using recommendation degree map for 3D outdoor modeling

2007

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We propose a support system of range data acquisition by a laser rangefinder for wide area outdoor modeling in order to reduce un-observed portions of generated model. The system presents the operator a recommendation degree map which illustrates recommendation position of acquisition of range data in the objective area. The operator decides a next acquisition position in consideration of movement distance of sensor system and recommendation degrees of the map. The recommendation degree is computed by measurement density as the index. The recommendation degree at a position is given by the difference between measurement density acquired by rangefinder and measurement density estimated by the system in reachable area of the laser beams. The reachable area of the laser beams is estimated by using a 3D model generated from the acquired range data. The system computes the measurement density by the reachable area of the laser beams. The recommendation degrees in the objective area are computed by the model generated from range data whenever a range data is acquired. Moreover, the system judges whether overlapping portions of the range data can be acquired for the registration by ICP algorithm from a work area which the sensor system can enter.

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3D Modeling of Outdoor Environments by Integrating Omnidirectional Range and Color Images

Cited by 21 publications

References 17 publications

Automatic Registration of Terrestrial Laser Scanner Point Clouds Using Natural Planar Surfaces

Automatic Registration of Terrestrial Laser Scanner Point Clouds Using Natural Planar Surfaces

3D Scene Reconstruction from Multiple Spherical Stereo Pairs

Data acquiring support system using recommendation degree map for 3D outdoor modeling

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