The Visual Computer: International Journal of Computer Graphics

This paper presents a novel high-order graph convolutional network (GCN) for pedestrian trajectory prediction. Specifically, the walking state of a target pedestrian depends on both its historical trajectory, which encodes its speed, walking ...$$

In a previous paper (Lipovetsky and Dyn in Comput Aided Geom Des 48:36–48, 2016), we introduced a weighted binary average of two 2D point-normal pairs, termed circle average, and investigated subdivision schemes based on it. These schemes refine ...

Summarization is important in sports video analysis; it gives a more compact and interesting representation of content. The automatic cricket video summarization is more challenging as it contains several rules and longer match duration. In this ...$\mathrm{}$$\mathrm{}$

Motivated by how humans perceive geometry and color to recognize objects, we propose a boundary embedded attentional convolution (BEACon) network for point cloud instance segmentation. At the core of BEACon, we introduce the attentional weight in ...

Glaucoma disease is affecting a large community worldwide. It gradually affects the optic nerve and may cause partial or complete vision loss. Glaucoma happens due to an increase in the fluid pressure inside the optic nerve, which is also known as ...

As an important task in scene understanding, semantic segmentation requires a large amount of computation to achieve high performance. In recent years, with the rise of autonomous systems, it is crucial to make a trade-off in terms of accuracy and ...

Manual harvesting of loose fruits in the oil palm plantation is both time consuming and physically laborious. Automatic harvesting system is an alternative solution for precision agriculture which requires accurate visual information of the ...

The presence of haze affects a multitude of applications that require detection of image features, such as target tracking, object recognition and camera-based advanced driving assistance systems. In this paper, an optimization framework is ...${}_{\mathrm{}}$

This paper presents a method for detecting and tracking large number of arbitrary-oriented and densely aggregated microbes from image sequences captured under microscope. We first propose an integral channel feature (ICF)-based detector which is ...

Human recognition systems based on biometrics are much in demand due to increasing concerns of security and privacy. The human ear is unique and useful for recognition. It offers numerous advantages over popular biometrics traits face, iris, and ...

Human beings easily reconstruct the 3D pose of a human from a 2D image, but 3D human pose reconstruction (HPR) continues to exist as a challenging task for machines. Traditional methods can reconstruct the 3D pose from the image directly or from ...

Kernel sparse representation-based classification (KSRC) in compressive sensing represents one of the most interesting research areas in pattern recognition and image processing. Nevertheless, KSRC is subjected to some shortcomings. KSRC is greedy ...${}_{\mathrm{}}$${}_{\mathrm{}}$

Hard-joint localization in human pose estimation is a challenging task for some reasons, such as the disappearance of joint points caused by clothing and lighting, the shelter caused by complex environment and the destruction of dependence among ...

Face recognition is used in biometric systems to verify and authenticate an individual. However, most face authentication systems are prone to spoofing attacks such as replay attacks, attacks using 3D masks etc. Thus, the importance of face anti-...

In the task of semantic segmentation, researchers often use self-attention module to capture long-range contextual information. These methods are often effective. However, the use of the self-attention module will cause a problem that cannot be ...

Although convolutional neural networks (CNNs) show great abilities in image classification, improving their performance is still challenging for shallow networks. The redundancy of the network increases when more convolution kernels are adopted in ...$\mathrm{}$$\mathrm{}$

The conventional fuzzy c-means clustering (FCM) algorithm is sensitive to noise because no spatial information is taken into account. Many related algorithms reduce the influence of noise by adding local information to the objective function. ...

In the commonly used datasets of person re-identification, the image quality is not uniform. Most existing methods on person re-identification mainly focus on the challenges caused by occlusion, view and pose variations, ignoring the diversity of ...

Attention mechanism plays an essential role in many tasks such as image classification, object detection, and instance segmentation. However, existing methods typically assigned attention weights to feature maps of the previous layer. The kernels ...

Multi-view face generation from a single image is an essential and challenging problem. Most of the existing methods need to use paired images when training models. However, collecting and labeling large-scale paired face images could lead to high ...

Visual object tracking is a basic task in the field of computer vision. Despite the rapid development of visual object tracking, it is not reliable to use only visible light images for object tracking in some cases. Since visible light and thermal ...

This paper proposed a fast and efficient video de-hazing system with reduced computational complexity for real-time computer vision applications. Video de-hazing is an important task and extensively researched in image/video processing and ...

At present, the Chinese government is encouraging people to learn calligraphy; however, an automatic evaluation method for the results is not available. Calligraphy evaluation is challenging, because calligraphic characters are complex graphics ...

Iris segmentation plays a vital role in the iris recognition system. However, it faces many challenges in non-ideal situations. To improve the iris segmentation performance for possible mobile devices, this paper presents a light iris segmentation ...

Pose prediction is to predict future poses given a window of previous poses. In this paper, we propose a new problem that predicts poses using 3D positions of skeletal sequences.Different from the traditional pose prediction based on mocap frames, ...