Photo-Consistent Planar Patches from Unstructured Cloud of Points

Toldo, Roberto; Fusiello, Andrea

doi:10.1007/978-3-642-15555-0_43

Cited by 10 publications

(10 citation statements)

References 19 publications

(29 reference statements)

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“…After photo-adjustment the figure improves by about 4%. Figure 14: Running times of our method compared with [21]. The blue line plots the same data reported in Tab.…”

Section: Resultsmentioning

confidence: 95%

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Image-consistent patches from unstructured points with J-linkage

Toldo

Fusiello

2013

Image and Vision Computing

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Going from unstructured cloud of points to surfaces is a challenging problem. However, as points are produced by a structure-and-motion pipeline, image-consistency is a powerful clue that comes to the rescue. In this paper we present a method for extracting planar patches from an unstructured cloud of points, based on the detection of image-consistent planar patches with J-linkage, a robust algorithm for multiple models fitting. The method integrates several constraints inside J-linkage, optimizes the position of the points with regard to image-consistency and deploys a hierarchical processing scheme that decreases the computational load. With respect to previous work this approach has the advantage of starting from sparse data. Several results show the e↵ectiveness of the proposed approach.

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“…After photo-adjustment the figure improves by about 4%. Figure 14: Running times of our method compared with [21]. The blue line plots the same data reported in Tab.…”

Section: Resultsmentioning

confidence: 95%

“…= p 3.0 . Figure 14 compares the running time of this method (without photo-adjustment) with the sequential approach (as implemented in [21]): It clearly appears that the speed up gained by this approach is remarkable. Figure 12: Example of the e↵ect of the "opening" procedure.…”

Section: Hierarchical Processingmentioning

confidence: 99%

Image-consistent patches from unstructured points with J-linkage

Toldo

Fusiello

2013

Image and Vision Computing

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“…Given camera motion and 3D point cloud, early works on piecewiseplanar scene segmentation from multiple images [1,26] are based on line grouping and plane sweeping, whose complexity is prohibitive beyond a few images. More recently, [2] and [24] both combine the idea of random sampling consensus (RANSAC) with photometric consistency check to obtain piecewise planar scene models. However, the experiment results in both papers only involve simple examples with little non-planar structure.…”

Section: Related Workmentioning

confidence: 99%

“…In addition, their computational complexity is still too high for our purpose. For example, it is reported in [24] that it takes 14 hours to process a sequence consisting of 380 frames. Finally, planes extracted from 3D point clouds or depth maps have been recently explored to improve the performance of multi-view stereo (MVS) systems [21,8,9,20].…”

Section: Related Workmentioning

confidence: 99%

Plane-Based Content Preserving Warps for Video Stabilization

Zhou

Jin

2013

2013 IEEE Conference on Computer Vision and Pattern Recognition

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Recently, a new image deformation technique called content-preserving warping (CPW) has been successfully employed to produce the state-of-the-art video stabilization results in many challenging cases. The key insight of CPW is that the true image deformation due to viewpoint change can be well approximated by a carefully constructed warp using a set of sparsely constructed 3D points only. However, since CPW solely relies on the tracked feature points to guide the warping, it works poorly in large textureless regions, such as ground and building interiors. To overcome this limitation, in this paper we present a hybrid approach for novel view synthesis, observing that the textureless regions often correspond to large planar surfaces in the scene. Particularly, given a jittery video, we first segment each frame into piecewise planar regions as well as regions labeled as non-planar using Markov random fields. Then, a new warp is computed by estimating a single homography for regions belong to the same plane, while inheriting results from CPW in the non-planar regions. We demonstrate how the segmentation information can be efficiently obtained and seamlessly integrated into the stabilization framework. Experimental results on a variety of real video sequences verify the effectiveness of our method.

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“…Toldo et al proposed planar patch extraction using the J-linkage algorithm and reconstructed the scene with view clustering tree and hierarchical reconstruction [4]. 1 Google Sketchup, http://sketchup.google.com/ Some approaches have invoked the stronger Manhattan world assumption which states the world is piecewise planar and aligned to orthogonal axes.…”

Section: Introductionmentioning

confidence: 99%

Planar urban scene reconstruction from spherical images using facade alignment

Kim

Hilton

2013

Ivmsp 2013

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We propose a plane-based urban scene reconstruction method using spherical stereo image pairs. We assume that the urban scene consists of axis-aligned approximately planar structures (Manhattan world). Captured spherical stereo images are converted into six central-point perspective images by cubic projection and facade alignment. Facade alignment automatically identifies the principal planes direction in the scene allowing the cubic projection to preserve the plane structure. Depth information is recovered by stereo matching between images and independent 3D rectangular planes are constructed by plane fitting aligned with the principal axes. Finally planar regions are refined by expanding, detecting intersections and cropping based on visibility. The reconstructed model efficiently represents the structure of the scene and texture mapping allows natural walk-through rendering.

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Photo-Consistent Planar Patches from Unstructured Cloud of Points

Cited by 10 publications

References 19 publications

Image-consistent patches from unstructured points with J-linkage

Image-consistent patches from unstructured points with J-linkage

Plane-Based Content Preserving Warps for Video Stabilization

Planar urban scene reconstruction from spherical images using facade alignment

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