Understanding human actions in visual data is tied to advances in complementary research
areas including object recognition, human dynamics, domain adaptation and semantic …

As a result of several successful applications in computer vision and image processing,
sparse representation (SR) has attracted significant attention in multi-sensor image fusion …

Compared with radar and visible light imaging, infrared imaging has its own unique
advantages, and in recent years, it has become a topic of intense research interest. Robust …

Human activity recognition (HAR) is a complex and multifaceted problem. The research
community has reported numerous approaches to perform HAR. Along with HAR …

Recognizing human activities from video sequences or still images is a challenging task due
to problems, such as background clutter, partial occlusion, changes in scale, viewpoint …

In this paper, we focus on heterogeneous feature learning for RGB-D activity recognition.
Considering that features from different channels could share some similar hidden …

Within a large range of applications in computer vision, Human Action Recognition has
become one of the most attractive research fields. Ambiguities in recognizing actions does …

Multi-focus image fusion has emerged as a major topic in image processing to generate all-
focus images with increased depth-of-field from multi-focus photographs. Different …

Artificial intelligence and its subcategories of machine learning and deep learning are
gaining increasing importance and attention in the context of sports research. This has also …

In many large-scale video analysis scenarios, one is interested in localizing and recognizing
human activities that occur in short temporal intervals within long untrimmed videos. Current …