Face pose estimation in monocular images

People use orientation of their faces to convey rich, inter-personal information. For example, a person will direct his face to indicate who the intended target of the conversation is. Similarly in a conversation, face orientation is a non-verbal cue to listener when to switch role and start speaking, and a nod indicates that a person has understands, or agrees with, what is being said. Further more, face pose estimation plays an important role in human-computer interaction, virtual reality applications, human behaviour analysis, pose-independent face recognition, driver s vigilance assessment, gaze estimation, etc. Robust face recognition has been a focus of research in computer vision community for more than two decades. Although substantial research has been done and numerous methods have been proposed for face recognition, there remain challenges in this field. One of these is face recognition under varying poses and that is why face pose estimation is still an important research area. In computer vision, face pose estimation is the process of inferring the face orientation from digital imagery. It requires a serious of image processing steps to transform a pixel-based representation of a human face into a high-level concept of direction. An ideal face pose estimator should be invariant to a variety of image-changing factors such as camera distortion, lighting condition, skin colour, projective geometry, facial hairs, facial expressions, presence of accessories like glasses and hats, etc. Face pose estimation has been a focus of research for about two decades and numerous research contributions have been presented in this field. Face pose estimation techniques in literature have still some shortcomings and limitations in terms of accuracy, applicability to monocular images, being autonomous, identity and lighting variations, image resolution variations, range of face motion, computational expense, presence of facial hairs, presence of accessories like glasses and hats, etc. These shortcomings of existing face pose estimation techniques motivated the research work presented in this thesis. The main focus of this research is to design and develop novel face pose estimation algorithms that improve automatic face pose estimation in terms of processing time, computational expense, and invariance to different conditions

Eyes extraction from facial images using edge density

This paper proposes a novel method for eyes extraction in facial images using edge density information. The method is based on the observation that irrespective of skin colour, colour variations occur the most in the eye region. In the proposed method, edges are detected in the input facial image. Morphological dilation is applied twice and the holes are filled in the connected regions. This makes the high density edges regions appear as blobs. Certain shapes and geometrical rules are applied to these blobs to extract the eyes. The method was tested using images from the PICS facial images database. The accuracies of the initial blobs extraction and the final eyes extraction were 95% and 72% respectively

Face pose estimation from eyes and mouth

Face pose estimation plays an important role in human computer interaction, automatic human behaviour analysis, gaze estimation, virtual reality, pose independent face recognition, etc. Accuracy and speed are the most desirable features of a face pose estimation system. In this paper, a face pose estimation scheme based on the centres of the eyes and mouth is proposed. The proposed method is simple and is, therefore, very effective in terms of computation because it uses only three points, i.e., eyes and mouth centres. The use of only three points increases the pose estimation range and makes the method suitable for real time applications. Tests using the Pointing '04 database show that the proposed scheme is robust and fast

A hybrid method for eyes detection in facial images

This paper proposes a hybrid method for eyes localization in facial images. The novelty is in combining techniques that utilise colour, edge and illumination cues to improve accuracy. The method is based on the observation that eye regions have dark colour, high density of edges and low illumination as compared to other parts of face. The first step in the method is to extract connected regions from facial images using colour, edge density and illumination cues separately. Some of the regions are then removed by applying rules that are based on the general geometry and shape of eyes. The remaining connected regions obtained through these three cues are then combined in a systematic way to enhance the identification of the candidate regions for the eyes. The geometry and shape based rules are then applied again to further remove the false eye regions. The proposed method was tested using images from the PICS facial images database. The proposed method has 93.7% and 87% accuracies for initial blobs extraction and final eye detection respectively

Wet environmental conditions affecting narrow band on-body communication channel for WBANs

© 2018 Old City Publishing, Inc. Wireless Body Area Networks (WBANs) are rising as the key building blocks of next generation networks in modern health care systems. Research in recent years has focused on channel modelling, energy conservation and design of efficient Medium Access Control (MAC) schemes for WBANs. However, less attention has been paid to the on-body channel propagation analysis. This paper presents the propagation effects of wet clothing on the on-body channel at 0.9GHz, 1.8GHz and 2.5GHz and is germane to signal budgets in body-centric and mobile communication systems. A number of transmission measurements between simple monopoles above a square ground plane, placed on the opposing shoulder and hip, wearing single and multi-layered “rainwater wet” and dry cotton T-Shirts for standing, bending, torso left and right are used to gain insight into general levels of the effect of rainwater on propagation. Measured results are statistically processed to extract the level of transmission enhancement due to a wet on-body channel. Results show that wet clothing is generally beneficial to the channel at popular mobile communications frequencies

Design and SAR analysis of wearable antenna on various parts of human body, using conventional and artificial ground planes

This paper presents design and specific absorption rate analysis of a 2.4 GHz wearable patch antenna on a conventional and electromagnetic bandgap (EBG) ground planes, under normal and bent conditions. Wearable materials are used in the design of the antenna and EBG surfaces. A woven fabric (Zelt) is used as a conductive material and a 3 mm thicker Wash Cotton is used as a substrate. The dielectric constant and tangent loss of the substrate are 1.51 and 0.02 respectively. The volume of the proposed antenna is 113×96.4×3 mm3. The metamaterial surface is used as a high impedance surface which shields the body from the hazards of electromagnetic radiations to reduce the Specific Absorption Rate (SAR). For on-body analysis a three layer model (containing skin, fats and muscles) of human arm is used. Antenna employing the EBG ground plane gives safe value of SAR (i.e. 1.77W/kg2W/kg). The efficiency of the EBG based antenna is improved from 52 to 74%, relative to the conventional counterpart. The proposed antenna can be used in wearable electronics and smart clothing

Eyes extraction from facial images using edge density

This paper proposes a novel method for eyes extraction in facial images using edge density information. The method is based on the observation that irrespective of skin colour, colour variations occur the most in the eye region. In the proposed method, edges are detected in the input facial image. Morphological dilation is applied twice and the holes are filled in the connected regions. This makes the high density edges regions appear as blobs. Certain shapes and geometrical rules are applied to these blobs to extract the eyes. The method was tested using images from the PICS facial images database. The accuracies of the initial blobs extraction and the final eyes extraction were 95% and 72% respectively

Characterization of on-body communication channel for vertical and horizontal polarization of center fed dipole at GSM frequency

While designing a wearable antenna for on-body communications, particular importance is given to lessen the lossy effects of the human body on transmission coefficient. This paper presents experimental and simulation results for two different polarizations of center-fed dipole antenna on human body at mobile communication frequency. The isolated parameter is S21(dB). Early results suggest that vertical polarization of dipole gives better transmission coefficient than horizontal polarization

S1 Data -

This study evaluated the usability of a direct manipulation device (touchscreen) vs. indirect manipulation devices (mouse and touchpad) on the selected Microsoft (MS) Word tasks as per ISO-9241-11 standard. MS Word was taken as an example of a complex application. The tasks were evaluated in terms of touch-friendly or click-friendly using efficiency, effectiveness, and satisfaction parameters to propose a customized task menu. The experiment was conducted with fifty-four participants, divided into three MS Word usage-based expertise groups. Each participant performed fifty-six tasks using a mouse, a touchpad, and a touchscreen. To assess task-level usability, individual one-way ANOVAs were performed for each task to gauge both efficiency and effectiveness. It’s worth noting that the touchscreen significantly outperformed other input methods in just one specific task regarding effectiveness. Consequently, an ANCOVA was employed, with task completion time as the independent variable and the number of errors as a covariate, to further investigate effectiveness. A total of 19 (34%) of the total tasks were found to be significantly efficient with a mouse, while 21 (37.5%) were significantly efficient with a touchscreen. Based on the results, a customized menu is recommended for MS Word-like applications that combine actions in touch-friendly tasks and mouse-friendly tasks separately.</div

Expertise based analysis.

This study evaluated the usability of a direct manipulation device (touchscreen) vs. indirect manipulation devices (mouse and touchpad) on the selected Microsoft (MS) Word tasks as per ISO-9241-11 standard. MS Word was taken as an example of a complex application. The tasks were evaluated in terms of touch-friendly or click-friendly using efficiency, effectiveness, and satisfaction parameters to propose a customized task menu. The experiment was conducted with fifty-four participants, divided into three MS Word usage-based expertise groups. Each participant performed fifty-six tasks using a mouse, a touchpad, and a touchscreen. To assess task-level usability, individual one-way ANOVAs were performed for each task to gauge both efficiency and effectiveness. It’s worth noting that the touchscreen significantly outperformed other input methods in just one specific task regarding effectiveness. Consequently, an ANCOVA was employed, with task completion time as the independent variable and the number of errors as a covariate, to further investigate effectiveness. A total of 19 (34%) of the total tasks were found to be significantly efficient with a mouse, while 21 (37.5%) were significantly efficient with a touchscreen. Based on the results, a customized menu is recommended for MS Word-like applications that combine actions in touch-friendly tasks and mouse-friendly tasks separately.</div