The Visual Computer: International Journal of Computer Graphics

An existing approach to dynamic hand gesture recognition is to use multimodal-fusion CRNN (Convolutional Recurrent Neural Networks) on depth images and corresponding 2D hand skeleton coordinates. However, an underlying problem in this method is ...

Pixel art has evolved from a primitive computer image presentation to an independent digital art style. It is widely used on the internet, for graphic user interface (GUI) design, and game industries. Existing pixelation tools and algorithms ...

Single image super-resolution is a digital image processing technique that can obtain a corresponding high-resolution image from a low-resolution image. The growth of deep convolutional neural networks in the field of computer vision has greatly ...

Infrared imaging technology has attracted numerous interests in military, security, transportation, etc. However, infrared images suffer from low contrast and blurry detail, limiting its application. To handle these issues, this paper presents a ...

This paper proposes an unconstrained human gaze estimation approach for medium-distance scene based on monocular vision. A recurrent convolution neural network for gaze estimation is designed to construct the mapping relationship from the face ...

Depth completion, the task of predicting dense depth maps from given depth maps of sparse, is an important topic in computer vision. To cope with the task, both traditional image processing- based and data-driven deep learning-based algorithms ...

The aim of the reference-based image super-resolution (RefSR) is to reconstruct high-resolution (HR) when a reference (Ref) image with similar content as that of the low-resolution (LR) input is given. In the task, the quality of existing ...

Existing unpaired image enhancement approaches prefer to employ the traditional two-way generative adversarial network (GAN) framework, in which two convolutional neural network (CNN) generators are deployed for enhancement and degradation ...

In retinex model, images are considered as a combination of two components: illumination and reflectance. However, decomposing an image into the illumination and reflectance is an ill-posed problem. This paper presents a new approach to estimate ...

Deep learning algorithms have made significant progress for deblurring in dynamic scenes. However, most of the existing image deblurring methods use a single blurry image as the input of the algorithm, which limits the acquisition of information ...

Accurate recognition of pests can effectively reduce the negative impact of pests on the agricultural economy. The unprofessional shooting ways result in low-resolution images, which seriously influences the accuracy of pest recognition. The super-...

Recently, red-green-blue (RGB) and thermal (RGB-T) data have attracted considerable interest for semantic segmentation because they provide robust imaging under the complex lighting conditions of urban roads. Most existing RGB-T semantic ...

The correlation filtering method is one of the mainstream methods in the visual target tracking task. One of the reasons is that the introduction of cyclic samples facilitates the calculation of optimizing filters. But usual correlation filtering ...

Hyperspectral anomaly detection is an alluring topic in hyperspectral image processing. As one of the most famous hyperspectral anomaly detection algorithms, Reed-Xiaoli detector is widely studied since it is understandable and easy to implement. ...

Handwritten character recognition (HCR) is a challenging task because of high intra-class dissimilarity and high inter-class similarity among the character images. Therefore, the features that are used to represent the character images should be ...

In augmented reality applications it is essential to know the position and orientation of the user to correctly register virtual 3D content in the user’s field of view. For this purpose, visual tracking through simultaneous localization and ...

Advances in communication and information technologies have allowed for improvements in the distribution and management of several types of imaging in digital medical environments. The scientific literature has reported data hiding methods that ...

Tracker based on the Siamese network is an important research direction of target tracking. However, Siamese trackers have the problem of insufficient characteristic expression ability extensively. To improve the situation, we introduced the ...

The stacking pseudoinverse learning algorithm can effectively improve the classification accuracy of the model and reduce the training time. However, the effect of random projection blocks on the neural network is often ignored, which reduces the ...

The automatic detection of image orientation is an important part of computer vision research. It is widely used in a variety of intelligent devices and application software. In the existing research on orientation detection, low-level features ...

Detecting anomalous crowd behavioral patterns from videos is an important task in video surveillance and maintaining public safety. In this work, we propose a novel architecture to detect anomalous patterns of crowd movements via graph networks. ...

Recently, deep learning has become a hot topic in wide fields, especially in the computer vision that proved its efficiency in processing images. However, it tends to overfit or consumes a long learning time in many platforms. The causes behind ...

Blind image deblurring is a challenging image processing problem, and a proper solution for this problem has many applications in the real world. This is an ill-posed problem, as both the sharp image and blur kernel are unknown. The traditional ...$$

Recovery or filling in of missing pixels in damaged images is a challenging problem known as image inpainting. Many currently used techniques still suffer from artifacts and other visual defects. In the proposed inpainting approach, the authors ...

Semantic segmentation suffers from boundary shift and shape deformation problems due to the neglect of overall guidance information. Motivated by that the object boundaries have a stronger representation for overall information of target objects, ...

Faster region-based convolution neural network (Faster RCNN) architecture was proposed as an efficient object detection method, wherein a CNN is used to extract image features. However, CNNs require a large number of learning parameters, and an ...

Pedestrian tracking is highly relevant to the understanding of static and moving scenes in video sequences. The increasing demand for people’s safety and security has resulted in more research on intelligent visual surveillance in a wide range of ...

The image stitching process often produces many undesirable effects. Solving problems such as discontinuity and dislocation of pictures has always been the focus of people’s research. From the perspective of human vision, this dislocation ...