Visibility Constrained Generative Model for Depth-based 3D Facial Pose Tracking

In this paper, we propose a generative framework that unifies depth-based 3D facial pose tracking and face model adaptation on-the-fly, in the unconstrained scenarios with heavy occlusions and arbitrary facial expression variations. Specifically, we introduce a statistical 3D morphable model that flexibly describes the distribution of points on the surface of the face model, with an efficient switchable online adaptation that gradually captures the identity of the tracked subject and rapidly constructs a suitable face model when the subject changes. Moreover, unlike prior art that employed ICP-based facial pose estimation, to improve robustness to occlusions, we propose a ray visibility constraint that regularizes the pose based on the face model's visibility with respect to the input point cloud. Ablation studies and experimental results on Biwi and ICT-3DHP datasets demonstrate that the proposed framework is effective and outperforms completing state-of-the-art depth-based methods

Solar Energy Harvesting for Wireless Sensor Network

Typically wireless sensor motes are operated by using small batteries because batteries are small in size and able to provide the sufficient energy for the motes. However batteries could not sustain the energy for the motes to operate for a long period. This is because the degradation of batteries could reduce the useable lifetime of the motes system. Besides that, batteries have limited energy capacity which could used up eventually. Aside from relying on the batteries to power up motes, one of the way to sustain the system is to harvest the sources of energy from the environment such as light, vibration, and thermal. These energies are renewable energy which does not cause pollution to the environment. In this project, solar energy harvesting have been proposed to sustain the energy requirement for the motes to operate. Experiments have been conducted to observe the solar panel charging characteristic to improve the efficiency and effectiveness of charging circuit to minimize the power loss. There are three main element in solar energy harvesting which are photovoltaic (PV) modules, solar charge controller and also energy storage. Based on the calculation, suitable PV modules, charging circuit and batteries are determined. Maximum Power Point Tracking (MPPT) technique are used for the charging circuit to maximize the efficiency conversion of the energy harvested from solar panel to charge the rechargeable lithium ion battery

Spontaneous spatial fractals: universal contexts and applications

We report on our latest research in the field of spontaneous spatial fractal patterns. New analyses, results and potential applications are reported for nonlinear ring cavities and kaleidoscope laser systems

MVF-Net: Multi-View 3D Face Morphable Model Regression

We address the problem of recovering the 3D geometry of a human face from a set of facial images in multiple views. While recent studies have shown impressive progress in 3D Morphable Model (3DMM) based facial reconstruction, the settings are mostly restricted to a single view. There is an inherent drawback in the single-view setting: the lack of reliable 3D constraints can cause unresolvable ambiguities. We in this paper explore 3DMM-based shape recovery in a different setting, where a set of multi-view facial images are given as input. A novel approach is proposed to regress 3DMM parameters from multi-view inputs with an end-to-end trainable Convolutional Neural Network (CNN). Multiview geometric constraints are incorporated into the network by establishing dense correspondences between different views leveraging a novel self-supervised view alignment loss. The main ingredient of the view alignment loss is a differentiable dense optical flow estimator that can backpropagate the alignment errors between an input view and a synthetic rendering from another input view, which is projected to the target view through the 3D shape to be inferred. Through minimizing the view alignment loss, better 3D shapes can be recovered such that the synthetic projections from one view to another can better align with the observed image. Extensive experiments demonstrate the superiority of the proposed method over other 3DMM methods.Comment: 2019 Conference on Computer Vision and Pattern Recognitio

An awkward looking pilomatrixoma

Pilomatrixoma is a rare and benign skin tumor of the hair follicle that tends to develop in the head and neck area. We report a case and briefly review the literature.peer-reviewe

An adaptive framework for combating advanced persistent threats

Advanced persistent threats (APTs) pose a significant risk to nearly every organization. Due to the sophistication of these attacks, they can bypass existing security systems and largely infiltrate the target network. The prevention and detection of APT are challenging because attackers constantly change and evolve their attacking techniques and methods to stay undetected. As a result, APT often successfully compromises companies, organizations, or public authorities. This paper developed an adaptive security framework that continuously investigates the behavior of users of a network to protect it against threats. The framework constitutes of three main sections namely; Intrusion prevention, Intrusion detection, and Response to intrusions. The design model comprises the front end, middleware, and back end. The front end is implemented using HTML and Cascading Style Sheet (CSS) in Netbeans Integrated Development Environment (IDE) version 8.0.2. The middleware is implemented using Java Web of NetBeans IDE while the back end is implemented using MySQL server. The results show that the runtime security of the system is adapted according to the behavior patterns exhibited by the user hence, our system can detect zero-day attacks which signature-based intrusion detection systems cannot detect, thus protecting against these attacks. The work is recommended as a countermeasure against emerging persistent attacks