The utility of using inertial data for the structure-from-motion (SfM) problem is addressed. We show how inertial data can be used for improved noise resistance, reduction of inherent ambiguities, and handling of mixed-domain sequences. We also show that the number of feature points needed for accurate and robust SfM estimation can be significantly reduced when inertial data are employed. Cramé...

We have developed a method referred to as three-dimensional scanning force microscopy (3D-SFM) which enables us to visualize water distribution at a solid-liquid interface with an atomic-scale resolution in less than 1 min. The 3D-SFM image obtained at a mica-water interface visualizes 3D distributions of adsorbed water molecules above the center of hexagonal cavities and the laterally distribu...

Children’s speech poses challenges to speech recognition due to strong age-dependent anatomical variations and a lack of large, publicly-available corpora. In this paper we explore data augmentation for children’s speech recognition using stochastic feature mapping (SFM) to transform out-of-domain adult data for both GMM-based and DNN-based acoustic models. We performed experiments on the Engli...

We propose a novel algorithm that solves the Structure from Motion problem in a divide and conquer manner by exploiting its bipartite graph structure. Recursive partitioning has a rich history, stemming from sparse linear algebra and finite element methods, and are also appealing for solving large-scale SfM problems. However, an important and less explored question is how to generate good parti...

In Model-Based Diagnosis (MBD), the problem of computing a diagnosis in a strong-fault model (SFM) is computationally much harder than in a weak-fault model (WFM). For example, in propositional Horn models, computing the first minimal diagnosis in a weak-fault model (WFM) is in P but is NP-hard for strong-fault models. As a result, SFM problems of practical significance have not been studied in...

In this paper, a multi-focus image fusion method using Spatial Frequency Measurements (SFM) and Wavelet Packet was proposed. The proposed fusion approach, firstly, the two fused images were transformed and decomposed into sixteen subbands using Wavelet packet. Next, each subband was partitioned into subblocks and each block was identified the clearer regions by using the Spatial Frequency Measu...

The structure from motion (SfM) problem in computer vision is the problem of recovering the 3D structure of a stationary scene from a set of projective measurements, represented as a collection of 2D images, via estimation of motion of the cameras corresponding to these images. In essence, SfM involves the three main stages of (1) extraction of features in images (e.g., points of interest, line...

String kernels are attractive data analysis tools for analyzing string data. Among them, alignment kernels are known for their high prediction accuracies in string classifications when tested in combination with SVMs in various applications. However, alignment kernels have a crucial drawback in that they scale poorly due to their quadratic computation complexity in the number of input strings, ...

It is widely known that, for the affine camera model, both shape and motion data can be factorised directly from the measurement matrix containing the image coordinates of the tracked feature points. However, classical algorithms for Structure from Motion (SfM) are not robust: measurement outliers, that is, incorrectly detected or matched feature points can destroy the result. A few methods to ...

The Community Noise and Health Study conducted by Health Canada included randomly selected participants aged 18-79 yrs (606 males, 632 females, response rate 78.9%), living between 0.25 and 11.22 km from operational wind turbines. Annoyance to wind turbine noise (WTN) and other features, including shadow flicker (SF) was assessed. The current analysis reports on the degree to which estimating h...