Scene wireframes sketching for Unmanned Aerial Vehicles

Santos, Roi; Pardo, Xosé M.; Fdez-Vidal, Xosé R.

doi:10.1016/j.patcog.2018.09.017

Cited by 4 publications

(16 citation statements)

References 13 publications

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“…Note that this experiment takes into account just a the variation of the number of images in the dataset [22]. The results show that the method [2] obtains more usable results for a low number of images, and the results of method [1] are only more adequate than method [2] when the number of images gets close to a dozen. The spatial lines are colored attending to its distance to the surface of the Ground Truth mesh.…”

Section: How To Compare the Results With Ground Truth Meshesmentioning

confidence: 98%

“…There are real world applications of Computer Vision that does not always permit to obtain high definition pictures, in textured environments, without blurring and digital noise. For these applications it can be advantageous to estimate the camera extrinsics independently of any feature point 3D reconstruction [2]. Figure 3 shows a quantitative comparison of the methods [2] and [1] with just 6 and 8 images chosen from the dataset.…”

Section: How To Compare the Results With Ground Truth Meshesmentioning

confidence: 99%

“…For these applications it can be advantageous to estimate the camera extrinsics independently of any feature point 3D reconstruction [2]. Figure 3 shows a quantitative comparison of the methods [2] and [1] with just 6 and 8 images chosen from the dataset. Figure 4 increases the number of images to 10 and 12.…”

Section: How To Compare the Results With Ground Truth Meshesmentioning

confidence: 99%

“…Segment's endpoint location are noticeably less accurate than a rotation and scale invariant feature point. Employing line endpoints as the sole set of geometrical constraints in the adjustment might not be Figure from [2]. Graphic representation of the 3D abstraction layer of the method.…”

Section: Bundle Adjustment For Line Segmentsmentioning

confidence: 99%

“…This permits higher accuracy in the 3D reconstructions than using solely straight lines. A different approach employs only straight line segment correspondences in the reconstruction, independently of point based 3D reconstructions [2]. This approach has been proved advantageous over the first one in scenarios where not enought feature points can be accurately put in correspondence between the different views.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Build 3D Abstractions with Wireframes

Mateos

Pardo

Fdez-Vidal

2021

Applications of Pattern Recognition

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This chapter serves as an introduction to 3D representations of scenes or Structure From Motion (SfM) from straight line segments. Lines are frequently found in captures of man-made environments, and in nature are mixed with more organic shapes. The inclusion of straight lines in 3D representations provide structural information about the captured shapes and their limits, such as the intersection of planar structures. Line based SfM methods are not frequent in the literature due to the difficulty of detecting them reliably, their morphological changes under changes of perspective and the challenges inherent to finding correspondences of segments in images between the different views. Additionally, compared to points, lines add the dimensionalities carried by the line directions and lengths, which prevents the epipolar constraint to be valid along a straight line segment between two different views. This chapter introduces the geometrical relations which have to be exploited for SfM sketch or abstraction based on line segments, the optimization methods for its optimization, and how to compare the experimental results with Ground-Truth measurements.

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