Visual designers and artists may benefit from understanding computer colour models such as the RGB colour cube. Such an understanding may foster reasoned colour selection and design decisions for the RGB environment. The goal of this research is to examine the RGB colour cube and to explore its potential as a colour design tool. In order to achieve such objectives, visualization methods were de...

Depth can complement RGB with useful cues about object volumes and scene layout. However, RGB-D image datasets are still too small for directly training deep convolutional neural networks (CNNs), in contrast to the massive monomodal RGB datasets. Previous works in RGB-D recognition typically combine two separate networks for RGB and depth data, pretrained with a large RGB dataset and then fine ...

Although red giants deplete lithium on their surfaces, some giants are Li-rich. Intermediate-mass asymptotic giant branch (AGB) stars can generate Li through the Cameron–Fowler conveyor, but the existence of Li-rich, low-mass red giant branch (RGB) stars is puzzling. Globular clusters are the best sites to examine this phenomenon because it is straightforward to determine membership in the clus...

Traditional indoor laser scanning trolley/backpacks with multi-laser scanner, panorama cameras, and an inertial measurement unit (IMU) installed are a popular solution to the 3D indoor mapping problem. However, the cost of those mapping suits is quite expensive, and can hardly be replicated by consumer electronic components. The consumer RGB-Depth (RGB-D) camera (e.g., Kinect V2) is a low-cost ...

We present a novel method for the interactive markerless reconstruction of human heads using a single commodity RGB-D sensor. Our entire reconstruction pipeline is implemented on the GPU and allows to obtain high-quality reconstructions of the human head using an interactive and intuitive reconstruction paradigm. The core of our method is a fast GPU-based non-linear Quasi-Newton solver that all...

Convolutional neural networks (CNN) are limited by the lack of capability to handle geometric information due to the fixed grid kernel structure. The availability of depth data enables progress in RGB-D semantic segmentation with CNNs. State-of-the-art methods either use depth as additional images or process spatial information in 3D volumes or point clouds. These methods suffer from high compu...

The ego-motion of a moving RGB-Z sensor is computed using combined range flow and optical flow pixel constraints. The emphasis of the work is on computationally cheap yet accurate estimation of inter-frame translation and rotation parameters using a linear small rotation model. To ensure accurate inter-frame motion estimates, an iterative form of the estimator is developed which repeatedly warp...

We have applied a new method to analyze the horizontal branch (HB) morphology in relation to the distribution of stars near the red giant branch (RGB) tip for the globular clusters M22, M5, M68, M107, M72, M92, M3 and 47 Tuc. This new method permits determination of the cluster ages to greater accuracy than conventional isochrone fitting. Using the method in conjunction with our new high-qualit...

Obstacle avoidance is a fundamental requirement for autonomous robots which operate in, and interact with, the real world. When perception is limited to monocular vision avoiding collision becomes significantly more challenging due to the lack of 3D information. Conventional path planners for obstacle avoidance require tuning a number of parameters and do not have the ability to directly benefi...