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Recent progress in synthetic aperture sonar (SAS) technology and processing has led to significant advances in underwater imaging, outperforming previously common approaches in both accuracy and efficiency. There are, however, inherent limitations to current SAS reconstruction methodology. In particular, popular and efficient Fourier domain SAS methods require a 2D interpolation which is often ill...
Many of the existing methods for learning joint embedding of images and text use only supervised information from paired images and its textual attributes. Taking advantage of the recent success of unsupervised learning in deep neural networks, we propose an end-to-end learning framework that is able to extract more robust multi-modal representations across domains. The proposed method combines representation...
In this paper, we propose a novel method to jointly solve scene layout estimation and global registration problems for accurate indoor 3D reconstruction. Given a sequence of range data, we first build a set of scene fragments using KinectFusion and register them through pose graph optimization. Afterwards, we alternate between layout estimation and layout-based global registration processes in iterative...
Fast and robust 3D reconstruction of facial geometric structure from a single image is a challenging task with numerous applications, but there exist two problems when applied "in the wild": the 3D estimates are unstable for different photos of the same subject; the 3D estimates are over-regularized and generic. In response, a robust method for regressing discriminative 3D morphable face...
We present a fragmented piece reconstruction method that enables all non-overlapping and randomly placed fragmented pieces to be identified and gathered piece-by-piece to be placed in the corresponding position. The proposed method can be applied in many other fields such as industrial automation, robot vision, archeology, and art restoration.
Visual Secret Sharing (VSS) is a type of cryptographic method used to secure digital media such as images by splitting it into n shares. Then, with k or more shares, the secret media can be reconstructed. Without the required number of shares, they are totally useless individually. The purpose of secret sharing methods is to reinforce the cryptographic approach from different points of failure as...
Robust and efficient image alignment remains a challenging task, due to the massiveness of images, great illumination variations between images, partial occlusion and corruption. To address these challenges, we propose an online image alignment method via subspace learning from image gradient orientations (IGO). The proposed method integrates the subspace learning, transformed IGO reconstruction and...
Surface reconstruction from a point cloud is a standard subproblem in many algorithms for dense 3D reconstruction from RGB images or depth maps. Methods, performing only local operations in the vicinity of individual points, are very fast, but reconstructed models typically contain lots of holes. On the other hand, regularized volumetric approaches, formulated as a global optimization, are typically...
For the restoration problem of shredded paper broken by shredder machines with the same marginal feature, a new method based on ant colony algorithm with classification is proposed in this paper. Firstly, shredded paper feature vector can be extracted by image space information. Secondly, the similar matrix and the marginal distance matrix are defined by the feature vector and left-right part image...
Shape reconstruction techniques using structured light have been widely researched and developed due to their robustness, high precision, and density. Because the techniques are based on decoding a pattern to find correspondences, it implicitly requires that the projected patterns be clearly captured by an image sensor, i.e., to avoid defocus and motion blur of the projected pattern. Although intensive...
Shape from focus technique can be used in the computer monocular vision, which is widely applied in the smart transportation. In this study, we proposed a novel directional statistics based focus measure for shape from focus computation. We first compute the standard deviation σ and the mean value μ in the directional neighborhood. Then use the σ/μ as the focus measure to estimate the shape. The proposed...
Applications of compressive sensing (CS) theory involve recovering sparse signals by solving ℓ1 norm regularized objective functions. Due to discontinuity of ℓ1-norm, usage of gradient based algorithm for reconstruction of sparse signals is not possible. Different smooth surrogate functions have been used to approximate ℓ1 norm. This article presents a performance comparison of two such surrogate...
Multibaseline phase unwrapping (PU) is a critical processing procedure of multibaseline synthetic aperture radar interferometry (InSAR). The presence of phase noise makes Chinese remainder theorem (CRT) method not robust enough and inapplicable in practical cases. In this letter, a method based on a closed-form robust Chinese remainder theorem (CFRCRT) is presented to improve the noise robustness...
In this paper, a new video super-resolution reconstruction (SRR) method with improved robustness to outliers is proposed. By studying the proximal point cost function representation of the R-LMS iterative equation, a better understanding of its performance is attained, which allows us to devise a new algorithm with improved robustness, while maintaining comparable quality and computational cost. Monte...
Video-based face recognition (FR) is a challenging task in real-world applications. In still-to-video FR, probe facial regions of interest (ROIs) are typically captured with lower-quality video cameras under unconstrained conditions, where facial appearances vary according to pose, illumination, scale, expression, etc. These video ROIs are typically compared against facial models designed with high-quality...
RGB-D scanning of indoor environments is important for many applications, including real estate, interior design, and virtual reality. However, it is still challenging to register RGB-D images from a hand-held camera over a long video sequence into a globally consistent 3D model. Current methods often can lose tracking or drift and thus fail to reconstruct salient structures in large environments...
The 3D shapes of faces are well known to be discriminative. Yet despite this, they are rarely used for face recognition and always under controlled viewing conditions. We claim that this is a symptom of a serious but often overlooked problem with existing methods for single view 3D face reconstruction: when applied in the wild, their 3D estimates are either unstable and change for different photos...
Highly effective optimization frameworks have been developed for traditional multiview stereo relying on lambertian photoconsistency. However, they do not account for complex material properties. On the other hand, recent works have explored PDE invariants for shape recovery with complex BRDFs, but they have not been incorporated into robust numerical optimization frameworks. We present a variational...
This paper presents a novel method for detecting pedestrians under adverse illumination conditions. Our approach relies on a novel cross-modality learning framework and it is based on two main phases. First, given a multimodal dataset, a deep convolutional network is employed to learn a non-linear mapping, modeling the relations between RGB and thermal data. Then, the learned feature representations...
Structure-from-Motion (SfM) methods can be broadly categorized as incremental or global according to their ways to estimate initial camera poses. While incremental system has advanced in robustness and accuracy, the efficiency remains its key challenge. To solve this problem, global reconstruction system simultaneously estimates all camera poses from the epipolar geometry graph, but it is usually...
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