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Analysis of human interaction is one important research topic of human motion analysis. It has been studied either using first-person vision (FPV) or third-person vision (TPV). However, the joint learning of both types of vision has so far ...

• A consensus model based on endo-confidence is constructed.
• Double hierarchical clustering is introduced in the consensus reaching process. Firstly, the experts are classified according to their evaluations (the numerical evaluations ...

With the development of novel technological and societal paradigms, consensus in multi-attribute large-scale group decision making is of great significance. The confidence derived by evaluation is considered in this paper and it is named as endo-...

Skeleton data is widely used in human action recognition for easy access, computational efficiency and environmental robustness. Recently, encoding skeleton sequences into color images becomes a popular preprocessing procedure to make use of the ...

This paper proposes a new graph convolutional operator called central difference graph convolution (CDGC) for skeleton based action recognition. It is not only able to aggregate node information like a vanilla graph convolutional operation but also ...

Extracting information and knowledge from users’ online activity is of great significance for a variety of practical purposes. Yet, existing research suffers from limitations including requiring prior knowledge and poor ...

• This study investigates a distinctive type of online crowd-sourced activities.
• ...

Albeit great success has been achieved in image defocus blur detection, there are still several unsolved challenges, e.g., interference of background clutter, scale sensitivity and missing boundary details of blur regions. To deal with these issues, we ...

Generation of a 3D model of an object from multiple views has a wide range of applications. Different parts of an object would be accurately captured by a particular view or a subset of views in the case of multiple views. In this paper, a novel coarse-to-...

Multi-criteria decision making (MCDM) is a common method used to solve complex decision-making problems. One such method, TODIM (TOmada de Decisão Iterativa Multicritério), is derived from prospect theory, which considers the ...

• Present the literature review of the extensions of fuzzy TODIM.
• Give extensions ...

The Sussex-Huawei Locomotion Challenge (SHL) 2021 organized at the HASCA Workshop of UbiComp 2021 is to recognize human activity by using GPS reception, GPS location, Wifi reception and GSM cell tower scans data. Compared with the previous challenge, ...

The multipath effect inhibits the centimeter-accuracy positioning in Android smart devices which have poor multipath suppression. We investigate the multipath extraction effectiveness in the reduction of the noise of low-accuracy positioning ...

Existing unsupervised visual odometry (VO) methods either match pairwise images or integrate the temporal information using recurrent neural networks over a long sequence of images. They are either not accurate, time-consuming in training or error ...

The past several years have witnessed increasing research interest on covariance-based feature representation. Originally proposed as a region descriptor, it has now been used as a general representation in various recognition tasks, demonstrating ...

This paper proposes a novel Semi-Dynamic Hypergraph Neural Network (SD-HNN) to estimate 3D human pose from a single image. SD-HNN adopts hypergraph to represent the human body to effectively exploit the kinematic constrains among adjacent and non-adjacent ...

This paper presents a study of automatic design of neural network architectures for skeleton-based action recognition. Specifically, we encode a skeleton-based action instance into a tensor and carefully define a set of operations to build two ...

RGB-D based action recognition is attracting more and more attention in both the research and industrial communities. However, due to the lack of training data, pre-training based methods are popular in this field. This paper presents a review of ...

With the advance of deep learning, deep learning based action recognition is an important research topic in computer vision. The skeleton sequence is often encoded into an image to better use Convolutional Neural Networks (ConvNets) such as Joint ...

This paper presents a new perspective to formulate unsupervised domain adaptation as a multi-task learning problem. This formulation removes the commonly used assumption in the classifier-based adaptation approach that a shared ...

• Present an end-to-end trainable deep architecture to learn an attentive dynamic map (ADM).

This paper presents a novel end-to-end trainable deep architecture to learn an attentive dynamic map (ADM) for understanding human motion from skeleton data. An ADM intends not only to capture the dynamic information over the period of ...

It is a big challenge for resource-limited mobile devices (MDs) to execute various complex and energy-consumed mobile applications. Fortunately, as a novel computing paradigm, edge computing (MEC) can provide abundant computing resources to ...

• We model the security services overhead under different performance parameters.
• A SEECO strategy is proposed to minimize the device energy with the security and deadline constrains.
• The GA and its coding strategy are devised to ...

This paper presents a new vision-based method for real-time assessment of upper-body postures of a subject who is sitting in front of a desk studying or operating a computer. Unlike most existing vision-based methods that perform offline assessment from ...