Installing flexible oil pipes in deep underwater environments is a risky operation, which is currently monitored by manually comparing the geometric conditions to the simulated studies. In order to avoid this error-prone assessment, this paper proposes an algorithm to track and reconstruct the pipe medial axis using stereo cameras. By taking advantage of the scenario illumination and the pipe texture, it is possible to devise an energy maximization approach that efficiently tracks the pipe. The reconstruction technique is an enhancement over a state-of-the-art B-spline reconstruction algorithm, specializing it for plane curves. Experiments on synthetic and laboratory videos report a very low mean tracking and reconstruction errors, while there are strong evidences of the robustness on a real scenario.

This paper presents a novel segmentation technique for flexible pipes in deep underwater environments. It consists in finding regions of the pipe denominated vertebrae and has three stages. Firstly, the input image is pre-processed to reduce noise. Secondly, the pre-processed image is binarized by the proposed Multi-level Topological Binarization technique, resulting in an image which highlights (in white) the regions that are potential vertebrae (the blobs). Lastly, the pipe is segmented by finding the best sequence of blobs that fulfills a set of restrictions inherent to a pipe. For improving the technique robustness, an alternating pattern of white (a vertebra) and black regions is marked on the pipe. Results show that the proposed technique can segment pipes even under harsh conditions such as: low contrast between pipe and background; uneven illumination of the pipe; and high level of noise due to floating particles. In particular, the proposed binarization technique achieves valuable results without any parameter, whereas state-of-the-art techniques did not achieve the same quality even after their parameters were fine-tuned for each condition. Two blurring filters are used for pre-processing input image: a bilateral filter [5] removes small particles floating around, while preserving the vertebrae’s edges; and a Gaussian filter uniformly smooths the images. The proposed binarization technique finds peaks in the pre-processed image. This is done by slicing the image into a number of slices si,b (i is its index and b is its level). A tree of slices is then constructed by hierarchically connecting nodes of consecutive levels (Figure 1a). Intuitively speaking, peaks are prominences similar to the first one exhibited in Figure 1b. More formally, a peak is a sequence of nodes denoted by P = {nk}k=1 = n1,n2, . . . ,nm, such that: nm is a leaf node of the tree; nk, such that 1≤ k < m, is the parent node of nk+1; n1 is the only element that has a brother node, or n1 is the only element that has a parent with genus greater than zero, or n1 is the root node. Nodes n1 and nm are respectively named the base and the top of a peak. Given a tree of slices, one has to traverse it from leaves to root in order to find its peaks. For example, Figure 1a contains three peaks: the first one is P′ = s1,2,s1,3; the second is P′′ = s2,2,s2,3; and the third is P′′′ = s3,2,s3,3,s1,4.

This paper presents a solution for the photorealistic rendering of synthetic objects into dynamic real scenes, in Augmented Reality applications. In order to achieve this goal, an Image Based Lighting approach is used, where environment maps with different levels of glossiness are generated for each virtual object in the scene at every frame. Due to this, illumination effects, such as color bleeding and specular reflections, can be simulated for virtual objects in a consistent way. A unifying sampling method for the spherical harmonics transformation pass is also used. It is independent of map format and does not need to apply different weights for each sample. The developed technique is combined with an extended version of Lafortune Spatial BRDF, featuring Fresnel effect and an innovative tangent rotation parameterization. The solution is evaluated in various Augmented Reality case studies, where other features like shadowing and lens effects are also exploited.

This paper presents a solution for the photorealistic rendering of synthetic objects into dynamic real scenes, in Augmented Reality applications. In order to achieve this goal, an Image Based Lighting approach is proposed, where environment maps with different levels of glossiness are generated for each virtual object in the scene at every frame. Due to this, illumination effects, such as color bleeding and specular reflections, can be simulated for virtual objects in a consistent way, even under the presence of scene changes. A unifying sampling method for the spherical harmonics transformation pass is also used. It is independent of map format and does not need to apply different weights for each sample. The developed technique is combined with an extended version of Lafortune Spatial BRDF, featuring Fresnel effect and an innovative tangent rotation parameterization. The solution is evaluated in various Augmented Reality case studies, where other features like shadowing and lens effects are also exploited.