A survey on mouth modeling and analysis for Sign Language recognition

© 2015 IEEE.Around 70 million Deaf worldwide use Sign Languages (SLs) as their native languages. At the same time, they have limited reading/writing skills in the spoken language. This puts them at a severe disadvantage in many contexts, including education, work, usage of computers and the Internet. Automatic Sign Language Recognition (ASLR) can support the Deaf in many ways, e.g. by enabling the development of systems for Human-Computer Interaction in SL and translation between sign and spoken language. Research in ASLR usually revolves around automatic understanding of manual signs. Recently, ASLR research community has started to appreciate the importance of non-manuals, since they are related to the lexical meaning of a sign, the syntax and the prosody. Nonmanuals include body and head pose, movement of the eyebrows and the eyes, as well as blinks and squints. Arguably, the mouth is one of the most involved parts of the face in non-manuals. Mouth actions related to ASLR can be either mouthings, i.e. visual syllables with the mouth while signing, or non-verbal mouth gestures. Both are very important in ASLR. In this paper, we present the first survey on mouth non-manuals in ASLR. We start by showing why mouth motion is important in SL and the relevant techniques that exist within ASLR. Since limited research has been conducted regarding automatic analysis of mouth motion in the context of ALSR, we proceed by surveying relevant techniques from the areas of automatic mouth expression and visual speech recognition which can be applied to the task. Finally, we conclude by presenting the challenges and potentials of automatic analysis of mouth motion in the context of ASLR

Consideration of some factors affecting low-frequency fuselage noise transmission for propeller aircraft

Possible reasons for disagreement between measured and predicted trends of sidewall noise transmission at low frequency are investigated using simplified analysis methods. An analytical model combining incident plane acoustic waves with an infinite flat panel is used to study the effects of sound incidence angle, plate structural properties, frequency, absorption, and the difference between noise reduction and transmission loss. Analysis shows that these factors have significant effects on noise transmission but they do not account for the differences between measured and predicted trends at low frequencies. An analytical model combining an infinite flat plate with a normally incident acoustic wave having exponentially decaying magnitude along one coordinate is used to study the effect of a localized source distribution such as is associated with propeller noise. Results show that the localization brings the predicted low-frequency trend of noise transmission into better agreement with measured propeller results. This effect is independent of low-frequency stiffness effects that have been previously reported to be associated with boundary conditions

Studies of noise transmission in advanced composite material structures

Noise characteristics of advanced composite material fuselages were discussed from the standpoints of applicable research programs and noise transmission theory. Experimental verification of the theory was also included

Acoustic fatigue: Overview of activities at NASA Langley

A number of aircraft and spacecraft configurations are being considered for future development. These include high-speed turboprop aircraft, advanced vertical take-off and landing fighter aircraft, and aerospace planes for hypersonic intercontinental cruise or flight to orbit and return. Review of the acoustic environment expected for these vehicles indicates levels high enough that acoustic fatigue must be considered. Unfortunately, the sonic fatique design technology used for current aircraft may not be adequate for these future vehicles. This has resulted in renewed emphasis on acoustic fatigue research at the NASA Langley Research Center. The overall objective of the Langley program is to develop methods and information for design of aerospace vehicles that will resist acoustic fatigue. The program includes definition of the acoustic loads acting on structures due to exhaust jets of boundary layers, and subsequent determination of the stresses within the structure due to these acoustic loads. Material fatigue associated with the high frequency structural stress reversal patterns resulting from acoustic loadings is considered to be an area requiring study, but no activity is currently underway

On the performance of key pre-distribution for RPL-based IoT Networks

A core ingredient of the the Internet of Things (IoT) is the use of deeply embedded resource constrained devices, often connected to the Internet over Low Power and Lossy Networks. These constraints compounded by the need for unsupervised operation within an untrusted environment create considerable challenges for the secure operation of these systems. In this paper, we propose a novel method to secure an edge IoT network using the concept of key pre-distribution proposed by Eschenauer and Gligor in the context of distributed sensor networks. First, we investigate the performance of the unmodified algorithm in the Internet of Things setting and then analyse the results with a view to determine its performance and thus its suitability in this context. Specifically, we investigate how ring size influences performance in order to determine the required ring size that guarantees full connectivity of the network. We then proceed to propose a novel RPL objective function and associated metrics that ensure that any node that joins the network can establish secure communication with Internet destinations. , N., , H., , Th., , Th., , A., , P

Combining Dense Nonrigid Structure from Motion and 3D Morphable Models for Monocular 4D Face Reconstruction

This is the author accepted manuscript. The final version is available from ACM via the DOI in this record Monocular 4D face reconstruction is a challenging problem, especially in the case that the input video is captured under unconstrained conditions, i.e. "in the wild". The majority of the state-of-the-art approaches build upon 3D Morphable Modelling (3DMM), which has been proven to be more robust than model-free approaches such as Shape from Shading (SfS) or Structure from Motion (SfM). While offering visually plausible shape reconstruction results that resemble real faces, 3DMMs adhere to the model space learned from exemplar faces during the training phase, often yielding facial reconstructions that are excessively smooth and look too similar even across captured faces with completely different facial characteristics. This is due to the fact that 3DMMs are typically used as hard constraints on the reconstructed 3D shape. To overcome these limitations, in this paper we propose to combine 3DMMs with Dense Nonrigid Structure from Motion (DNSM), which is much less robust but has the potential of reconstructing fine details and capturing the subject-specific facial characteristics of every input. We effectively combine the best of both worlds by introducing a novel dense variational framework, which we solve efficiently by designing a convex optimisation strategy. In contrast to previous methods, we incorporate 3DMM as a soft constraint, penalizing both departure of reconstructed faces from the 3DMM subspace and variation of the identity component of the 3DMM over different frames of the input video. As demonstrated in qualitative and quantitative experiments, our method is robust, accurately estimates the 3D facial shape over time and outperforms other state-of-the-art methods of 4D face reconstruction

Secure routing in IoT networks with SISLOF

In this paper, we propose a modification of the RPL routing protocol by introducing the SISLOF Objective Function ensuring that only motes that share a suitable key can join the RPL routing table. This will ensure that all IoT network motes connect in a secure method. SISLOF uses the concept of key pre-distribution proposed by Eschenauer and Gligor in the context of the Internet of Things. First, we discuss related work that provide evidence that the key pre-distribution scheme in the context of the IoT with default RPL metrics fails to achieve the full network connectivity using the same ring size, however full time connectivity can be achieved but with a great cost in term of the large rings sizes. We introduce the SISLOF Objective Function and explain the modification it does to the RPL messages (DIO and DAO). We finally show the performance of the key pre-distribution in the context of the Internet of Things when SISLOF is used as the Objective Function of the RPL routing protocol

Noise Transmission Loss of a Rectangular Plate in an Infinite Baffle

An improved analytical procedure was developed that allows for the efficient calculation of the noise transmission characteristics of a finite rectangular plate. Both isotropic and symmetrically laminated composite plates are considered. The plate is modeled with classic thin-plate theory and is assumed to be simply supported on all four sides. The incident acoustic pressure is assumed to be a plane wave impinging on the plate at an arbitrary angle. The reradiated pressure is assumed to be negligible compared with the blocked pressure, and the plate vibrations are calculated by a normal-mode approach. A Green's function integral equation is used to link the plate vibrations to be transmitted far-field sound waves, and transmission loss is calculated from the ratio of incident to transmitted acoustic powers. The result is a versatile research and engineering analysis tool that predicts noise transmission loss and enables the determination of the modal behavior of the plate

Public goods: using pervasive computing to inspire grassroots activism

Pervasive computing technology enables social mapping and sharing of local knowledge to create relationships beyond established social and cultural boundaries; it also enables the development of new practices around place, identity, and community. For more than a decade, the authors have explored the potential costs and benefits of using pervasive computing to facilitate codiscovery with communities across London, with the aim of supporting grassroots activities that help urban communities take action toward environmental sustainability. A core ingredient of these explorations is the making of artifacts to provide both the focus for communal experiences and a way to create public goods--that is, tangible representations of the intangible things we value most about our communities. Specific projects explore alternative material representations of stories, skills, games, songs, techniques, memories, hyper-local lore, and experiential knowledge of the environment. In this article, the authors present work that investigates how public goods can provide the focus for the development of grassroots community groups focused on hyper-local concerns. They also show how creating objects constructed to communicate the activist message of these communities in a tangible manner provides more affective and illustrative ways to facilitate the codiscovery of uncommon insights. This article is part of a special issue on pervasive analytics and citizen science

Face flow

In this paper, we propose a method for the robust and efficient computation of multi-frame optical flow in an expressive sequence of facial images. We formulate a novel energy minimisation problem for establishing dense correspondences between a neutral template and every frame of a sequence. We exploit the highly correlated nature of human expressions by representing dense facial motion using a deformation basis. Furthermore, we exploit the even higher correlation between deformations in a given input sequence by imposing a low-rank prior on the coefficients of the deformation basis, yielding temporally consistent optical flow. Our proposed model-based formulation, in conjunction with the inverse compositional strategy and low-rank matrix optimisation that we adopt, leads to a highly efficient algorithm for calculating facial flow. As experimental evaluation, we show quantitative experiments on a challenging novel benchmark of face sequences, with dense ground truth optical flow provided by motion capture data. We also provide qualitative results on a real sequence displaying fast motion and occlusions. Extensive quantitative and qualitative comparisons demonstrate that the proposed method outperforms state-of-the-art optical flow and dense non-rigid registration techniques, whilst running an order of magnitude faster