Skip to main content

Research Repository

Advanced Search

Outputs (64)

Two-stage human verification using HandCAPTCHA and anti-spoofed finger biometrics with feature selection (2021)
Journal Article
Bera, A., Bhattacharjee, D., & Shum, H. P. (2021). Two-stage human verification using HandCAPTCHA and anti-spoofed finger biometrics with feature selection. Expert Systems with Applications, 171, https://doi.org/10.1016/j.eswa.2021.114583

This paper presents a human verification scheme in two independent stages to overcome the vulnerabilities of attacks and to enhance security. At the first stage, a hand image-based CAPTCHA (HandCAPTCHA) is tested to avert automated bot-attacks on the... Read More about Two-stage human verification using HandCAPTCHA and anti-spoofed finger biometrics with feature selection.

Multi-task Deep Learning with Optical Flow Features for Self-Driving Cars (2020)
Journal Article
Hu, Y., Shum, H. P., & Ho, E. S. (2020). Multi-task Deep Learning with Optical Flow Features for Self-Driving Cars. IET Intelligent Transport Systems, 14(13), 1845-1854. https://doi.org/10.1049/iet-its.2020.0439

The control of self-driving cars has received growing attention recently. Although existing research shows promising results in the vehicle control using video from a monocular dash camera, there has been very limited work on directly learning vehicl... Read More about Multi-task Deep Learning with Optical Flow Features for Self-Driving Cars.

A Privacy-Preserving Efficient Location-Sharing Scheme for Mobile Online Social Network Applications (2020)
Journal Article
Bhattacharya, M., Roy, S., Mistry, K., Shum, H. P., & Chattopadhyay, S. (2020). A Privacy-Preserving Efficient Location-Sharing Scheme for Mobile Online Social Network Applications. IEEE Access, 8, https://doi.org/10.1109/access.2020.3043621

The rapid development of mobile internet technology and the better availability of GPS have made mobile online social networks (mOSNs) more popular than traditional online social networks (OSNs) over the last few years. They necessitate fundamental s... Read More about A Privacy-Preserving Efficient Location-Sharing Scheme for Mobile Online Social Network Applications.

A Quadruple Diffusion Convolutional Recurrent Network for Human Motion Prediction (2020)
Journal Article
Men, Q., Ho, E. S., Shum, H. P., & Leung, H. (2021). A Quadruple Diffusion Convolutional Recurrent Network for Human Motion Prediction. IEEE Transactions on Circuits and Systems for Video Technology, 31(9), 3417-3432. https://doi.org/10.1109/tcsvt.2020.3038145

Recurrent neural network (RNN) has become popular for human motion prediction thanks to its ability to capture temporal dependencies. However, it has limited capacity in modeling the complex spatial relationship in the human skeletal structure. In th... Read More about A Quadruple Diffusion Convolutional Recurrent Network for Human Motion Prediction.

Facial reshaping operator for controllable face beautification (2020)
Journal Article
Hu, S., Shum, H. P., Liang, X., Li, F. W., & Aslam, N. (2021). Facial reshaping operator for controllable face beautification. Expert Systems with Applications, 167, Article 114067. https://doi.org/10.1016/j.eswa.2020.114067

Posting attractive facial photos is part of everyday life in the social media era. Motivated by the demand, we propose a lightweight method to automatically and efficiently beautify the shapes of both portrait and non-portrait faces in photos, while... Read More about Facial reshaping operator for controllable face beautification.

LMZMPM: Local Modified Zernike Moment Per-unit Mass for Robust Human Face Recognition (2020)
Journal Article
Kar, A., Pramanik, S., Chakraborty, A., Bhattacharjee, D., Ho, E. S., & Shum, H. P. (2020). LMZMPM: Local Modified Zernike Moment Per-unit Mass for Robust Human Face Recognition. IEEE Transactions on Information Forensics and Security, 16, 495-509. https://doi.org/10.1109/tifs.2020.3015552

In this work, we proposed a novel method, called Local Modified Zernike Moment per unit Mass (LMZMPM), for face recognition, which is invariant to illumination, scaling, noise, in-plane rotation, and translation, along with other orthogonal and inher... Read More about LMZMPM: Local Modified Zernike Moment Per-unit Mass for Robust Human Face Recognition.

Cumuliform Cloud Formation Control using Parameter-Predicting Convolutional Neural Network (2020)
Journal Article
Zhang, Z., Ma, Y., Li, Y., Li, F. W., Shum, H. P., Yang, B., …Liang, X. (2020). Cumuliform Cloud Formation Control using Parameter-Predicting Convolutional Neural Network. Graphical Models, 111, Article 101083. https://doi.org/10.1016/j.gmod.2020.101083

Physically-based cloud simulation is an effective approach for synthesizing realistic cloud. However, generating clouds with desired shapes requires a time-consuming process for selecting the appropriate simulation parameters. This paper addresses su... Read More about Cumuliform Cloud Formation Control using Parameter-Predicting Convolutional Neural Network.

Sparse Metric-based Mesh Saliency (2020)
Journal Article
Hu, S., Liang, X., Shum, H. P., Li, F. W., & Aslam, N. (2020). Sparse Metric-based Mesh Saliency. Neurocomputing, 400, 11-23. https://doi.org/10.1016/j.neucom.2020.02.106

In this paper, we propose an accurate and robust approach to salient region detection for 3D polygonal surface meshes. The salient regions of a mesh are those that geometrically stand out from their contexts and therefore are semantically important f... Read More about Sparse Metric-based Mesh Saliency.

A Unified Deep Metric Representation for Mesh Saliency Detection and Non-rigid Shape Matching (2019)
Journal Article
Hu, S., Shum, H., Aslam, N., Li, F. W., & Liang, X. (2020). A Unified Deep Metric Representation for Mesh Saliency Detection and Non-rigid Shape Matching. IEEE Transactions on Multimedia, 22(9), 2278-2292. https://doi.org/10.1109/tmm.2019.2952983

In this paper, we propose a deep metric for unifying the representation of mesh saliency detection and non-rigid shape matching. While saliency detection and shape matching are two closely related and fundamental tasks in shape analysis, previous met... Read More about A Unified Deep Metric Representation for Mesh Saliency Detection and Non-rigid Shape Matching.

Spatio-temporal Manifold Learning for Human Motions via Long-horizon Modeling (2019)
Journal Article
Wang, H., Ho, E. S., Shum, H. P., & Zhu, Z. (2021). Spatio-temporal Manifold Learning for Human Motions via Long-horizon Modeling. IEEE Transactions on Visualization and Computer Graphics, 27(1), 216 - 227. https://doi.org/10.1109/tvcg.2019.2936810

Data-driven modeling of human motions is ubiquitous in computer graphics and vision applications. Such problems can be approached by deep learning on a large amount data. However, existing methods can be sub-optimal for two reasons. First, skeletal i... Read More about Spatio-temporal Manifold Learning for Human Motions via Long-horizon Modeling.

Interaction-Based Human Activity Comparison (2019)
Journal Article
Shen, Y., Yang, L., Ho, E. S., & Shum, H. P. (2020). Interaction-Based Human Activity Comparison. IEEE Transactions on Visualization and Computer Graphics, 26(8), 2620-2633. https://doi.org/10.1109/tvcg.2019.2893247

Traditional methods for motion comparison consider features from individual characters. However, the semantic meaning of many human activities is usually defined by the interaction between them, such as a high-five interaction of two characters. Ther... Read More about Interaction-Based Human Activity Comparison.

Automatic Musculoskeletal and Neurological Disorder Diagnosis With Relative Joint Displacement From Human Gait (2018)
Journal Article
Rueangsirarak, W., Zhang, J., Aslam, N., Ho, E. S., & Shum, H. P. (2018). Automatic Musculoskeletal and Neurological Disorder Diagnosis With Relative Joint Displacement From Human Gait. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 26(12), 2387-2396. https://doi.org/10.1109/tnsre.2018.2880871

Musculoskeletal and neurological disorders are common devastating companions of ageing, leading to a reduction in quality of life and increased mortality. Gait analysis is a popular method for diagnosing these disorders. However, manually analyzing t... Read More about Automatic Musculoskeletal and Neurological Disorder Diagnosis With Relative Joint Displacement From Human Gait.

Action Recognition From Arbitrary Views Using Transferable Dictionary Learning (2018)
Journal Article
Zhang, J., Shum, H. P., Han, J., & Shao, L. (2018). Action Recognition From Arbitrary Views Using Transferable Dictionary Learning. IEEE Transactions on Image Processing, 27(10), 4709-4723. https://doi.org/10.1109/tip.2018.2836323

Human action recognition is crucial to many practical applications, ranging from human-computer interaction to video surveillance. Most approaches either recognize the human action from a fixed view or require the knowledge of view angle, which is us... Read More about Action Recognition From Arbitrary Views Using Transferable Dictionary Learning.

Manifold Regularized Experimental Design for Active Learning (2016)
Journal Article
Zhang, L., Shum, H. P., & Shao, L. (2017). Manifold Regularized Experimental Design for Active Learning. IEEE Transactions on Image Processing, 26(2), 969-981. https://doi.org/10.1109/tip.2016.2635440

Various machine learning and data mining tasks in classification require abundant data samples to be labeled for training. Conventional active learning methods aim at labeling the most informative samples for alleviating the labor of the user. Many p... Read More about Manifold Regularized Experimental Design for Active Learning.

Validation of an ergonomic assessment method using Kinect data in real workplace conditions (2016)
Journal Article
Plantard, P., Shum, H. P., Le Pierres, A.-S., & Multon, F. (2017). Validation of an ergonomic assessment method using Kinect data in real workplace conditions. Applied Ergonomics: Human Factors in Technology and Society, 65, 562-569. https://doi.org/10.1016/j.apergo.2016.10.015

Evaluating potential musculoskeletal disorders risks in real workstations is challenging as the environment is cluttered, which makes it difficult to accurately assess workers' postures. Being marker-free and calibration-free, Microsoft Kinect is a p... Read More about Validation of an ergonomic assessment method using Kinect data in real workplace conditions.

Discriminative Semantic Subspace Analysis for Relevance Feedback (2016)
Journal Article
Zhang, L., Shum, H., & Shao, L. (2016). Discriminative Semantic Subspace Analysis for Relevance Feedback. IEEE Transactions on Image Processing, 25(3), 1275-1287. https://doi.org/10.1109/tip.2016.2516947

Content-based image retrieval (CBIR) has attracted much attention during the past decades for its potential practical applications to image database management. A variety of relevance feedback (RF) schemes have been designed to bridge the gap between... Read More about Discriminative Semantic Subspace Analysis for Relevance Feedback.

Kinect Posture Reconstruction Based on a Local Mixture of Gaussian Process Models (2015)
Journal Article
Liu, Z., Zhou, L., Leung, H., & Shum, H. P. (2016). Kinect Posture Reconstruction Based on a Local Mixture of Gaussian Process Models. IEEE Transactions on Visualization and Computer Graphics, 22(11), 2437-2450. https://doi.org/10.1109/tvcg.2015.2510000

Depth sensor based 3D human motion estimation hardware such as Kinect has made interactive applications more popular recently. However, it is still challenging to accurately recognize postures from a single depth camera due to the inherently noisy da... Read More about Kinect Posture Reconstruction Based on a Local Mixture of Gaussian Process Models.