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In this paper, the problem of age estimation is addressed based on two modalities: speech utterances and speakers' face images. The proposed age estimation framework employs the Shifted Covariates REgression Analysis for Multi-way data (SCREAM) model, which combines Parallel Factor Analysis 2 and Principal Covariates Regression. SCREAM is able to extract a few latent variables from multi-way data...
We present a novel approach for epoch estimation from the simple observation of the speech spectrum. Fundamental frequency (F0) of the speech signal and local variations around F0 are the characteristics of glottal excitation source. Extraction of this information from the speech spectrum can be used to estimate epochs (since higher harmonics interact with the vocal tract characteristics, they no...
Tracheoesophageal (TE) speech is generated by patients who have undergone a total laryngectomy where the larynx (voice box) is removed and replaced by a tracheoesophageal puncture. This work presents a novel low complexity algorithm to estimate the degree of severity of disordered TE speech. The proposed algorithm uses features which are computed from 32-ms voiced frames of the speech signal. A 21-st...
This study presents an age and gender estimation system that considers ethnic difference in face images using a Convolutional Neural Network(CNN) and Support Vector Machine(SVM). Most age and gender estimation systems using face images are trained on ethnicity-biased databases. Therefore, these systems show limited performance on face images of ethnic groups occupying a small proportion of the training...
Performance-based quality evaluation of database conceptual schemas is an important aspect of database design process. Performance of user applications strongly depends on the logical and physical database structures derived from the conceptual schemas. This work presents a complete process of performance-based quality evaluation of conceptual schemas. It shows how to express a conceptual database...
In this work we pursue a data-driven approach to the problem of estimating surface normals from a single intensity image, focusing in particular on human faces. We introduce new methods to exploit the currently available facial databases for dataset construction and tailor a deep convolutional neural network to the task of estimating facial surface normals in-the-wild. We train a fully convolutional...
Given a single photo of a room and a large database of furniture CAD models, our goal is to reconstruct a scene that is as similar as possible to the scene depicted in the photograph, and composed of objects drawn from the database. We present a completely automatic system to address this IM2CAD problem that produces high quality results on challenging imagery from interior home design and remodeling...
We propose the Component Bio-Inspired Feature (CBIF) with a moving segmentation scheme for age estimation. The CBIF defines a superset for the commonly used Bio-Inspired Feature (BIF) with more parameters and flexibility in settings, resulting in features with abundant characteristics. An in-depth study is performed for the determination of the parameters good for capturing age-related traits. The...
The acquisition of partial BRDF measurements using light field cameras and several illumination directions raises critical questions regarding the accuracy of inferences based on that data. Therefore, we attempt to verify the quality of the reconstruction of a full BRDF using partial input data. A dataset that provides a densely sampled BRDF was used, both in viewing and illumination directions. We...
In this paper we utilize the first large-scale "in-the-wild" (Aff-Wild) database, which is annotated in terms of the valence-arousal dimensions, to train and test an end-to-end deep neural architecture for the estimation of continuous emotion dimensions based on visual cues. The proposed architecture is based on jointly training convolutional (CNN) and recurrent neural network (RNN) layers,...
Automated affective computing in the wild is a challenging task in the field of computer vision. This paper presents three neural network-based methods proposed for the task of facial affect estimation submitted to the First Affect-in-the-Wild challenge. These methods are based on Inception-ResNet modules redesigned specifically for the task of facial affect estimation. These methods are: Shallow...
Over the last few years, increased interest has arisen with respect to age-related tasks in the Computer Vision community. As a result, several "in-the-wild" databases annotated with respect to the age attribute became available in the literature. Nevertheless, one major drawback of these databases is that they are semi-automatically collected and annotated and thus they contain noisy labels...
The Affect-in-the-Wild (Aff-Wild) Challenge proposes a new comprehensive benchmark for assessing the performance of facial affect/behaviour analysis/understanding 'in-the-wild'. The Aff-wild benchmark contains about 300 videos (over 2,000 minutes of data) annotated with regards to valence and arousal, all captured 'in-the-wild' (the main source being Youtube videos). The paper presents the database...
In recent years, services that use position estimation by Bluetooth Low Energy (BLE) are extensively being used. However, the technology itself is not used optimally owing to the high cost of installation at a base station. To solve this problem, we constructed and operated a system capable of visualizing the location information of a hotel key, and conducted an experiment to verify its functionality...
In database-driven spectrum sharing, despite the spectrum sharing policy given by a database, harmful interference can occur between a primary user (PU) and a secondary user (SU) due to the unexpected propagation paths. In a previous study, a primary exclusive region (PER) centered at a PU, wherein the SUs are forbidden to use the spectrum, has been proposed. However, the PER figure that efficiently...
This paper introduces a proposal of optimized management strategy to control a benchmark grid-connected microgrid consisting of some residential loads, some renewable generators (wind and PV), a genset generator, and a battery storage system. The proposal is to manage the microgrid according to the solution an optimization problem aimed to minimize an economic objective function. Microgrid performance...
In the context of a growing need for dedicated solutions in the field of human space mission support, this paper proposes an emotion assessment system and its dedicated implementation architecture. The proposed system is described and a pilot implementation of the emotion assessment system is developed utilizing open source software OpenFace for detection of key facial features, called Action Units...
With the prevalence of the online to offline (O2O) commerce, the short-distance instant logistics service becomes increasingly popular in China, which is a new logistics model emerged recently and provides timely logistics for O2O local life service. Being different from traditional logistics, extra waiting time generates when order's pick-up location arrival time is early than its pick-up ready time,...
Counterfeit integrated circuits (ICs) have posed a major security and safety threat on commercial and mission-critical systems. In this paper, we propose to develop a comprehensive counterfeit ICs detection and prevention strategy, consisting of an innovative multi-functional on-chip sensor and a related post-fabrication authentication methodology. We target at many counterfeit ICs including the recycled/remarked/out-of-spec...
Memcached is a widely used in-memory caching solution in large-scale searching scenarios. The most pivotal performance metric in Memcached is latency, which is affected by various factors including the workload pattern, the service rate, the unbalanced load distribution and the cache miss ratio. To quantitate the impact of each factor on latency, we establish a theoretical model for the Memcached...
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