Human activity recognition based on RGB-D data has received more attention in recent years. We propose a spatiotemporal feature named three-dimensional (3D) sparse motion scale-invariant feature transform (SIFT) from RGB-D data for activity recognition. First, we build pyramids as scale space for each RGB and depth frame, and then use Shi-Tomasi corner detector and sparse optical flow to quickl...

Hyperspectral cameras preserve the fine spectral details of scenes that are generally lost in the traditional RGB cameras due to the gross quantization of radiance. These details are desirable in numerous imaging applications, nevertheless the high cost of hyperspectral hardware and the associated physical constraints currently limit the pervasive use of hyperspectral imaging. We take a computa...

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...

introduction:.color is the first quality attribute of food evaluated by consumers, and is therefore an important quality component of food which influences consumer’s choice and preferences (maguire, 1994). color measurement of food products has been used as an indirect measure of other quality attributes such as flavor and contents of pigments because it is simpler, faster and correlates well ...

In this paper, we propose a correlated and individual multi-modal deep learning (CIMDL) method for RGB-D object recognition. Unlike most conventional RGB-D object recognition methods which extract features from the RGB and depth channels individually, our CIMDL jointly learns feature representations from raw RGB-D data with a pair of deep neural networks, so that the sharable and modalspecific ...

Many vision systems use skin detection as a principal component. Skin detection algorithms, normally evaluate a single and thus limited color model, such as HSV, Y CrCb, YUV, RGB, normalized RGB, etc. Their limited performance, however, suggests that they are looking at the incorrect color models. This paper describes a new constructive induction algorithm that creates adequate attributes for s...

In this paper, we propose a system to achieve Augmented Reality (AR) on a smartphone. In this system, we assume a fixed RGB-D camera connected to a server is installed in the environment, and perform AR based on the 3D environment shape got by the RGB-D camera in real-time. On the smartphone side, it sends the image captured by its camera, and receives the output image processed to perform AR b...