Fabio Lavagetto

The facial animation engine: toward a high-level interface for the design of MPEG-4 compliant animated faces

We propose a method for implementing a high-level interface for the synthesis and animation of animated virtual faces that is in full compliance with MPEG-4 specifications. This method allows us to implement the simple facial object profile and part of the calibration facial object profile. In fact, starting from a facial wireframe and from a set of configuration files, the developed system is capable of automatically generating the animation rules suited for model animation driven by a stream of facial animation parameters. If the calibration parameters (feature points and texture) are available, the system is able to exploit this information for suitably modifying the geometry of the wireframe and for performing its animation by means of calibrated rules computed ex novo on the adapted somatics of the model. Evidence of the achievable performance is reported at the end of this paper by means of figures showing the capability of the system to reshape its geometry according to the decoded MPEG-4 facial calibration parameters and its effectiveness in performing facial expressions.

MPEG-4: Audio/video and synthetic graphics/audio for mixed media

Abstract MPEG-4 addresses coding of digital hybrids of natural and synthetic, aural and visual (A/V) information. The objective of this synthetic/natural hybrid coding (SNHC) is to facilitate content-based manipulation, interoperability, and wider user access in the delivery of animated mixed media. SNHC will support non-real-time and passive media delivery, as well as more interactive, real-time applications. Integrated spatial-temporal coding is sought for audio, video, and 2D/3D computer graphics as standardized A/V objects. Targets of standardization include mesh-segmented video coding, compression of geometry, synchronization between A/V objects, multiplexing of streamed A/V objects, and spatial-temporal integration of mixed media types. Composition, interactivity, and scripting of A/V objects can thus be supported in client terminals, as well as in content production for servers, also more effectively enabling terminals as servers. Such A/V objects can exhibit high efficiency in transmission and storage, plus content-based interactivity, spatial-temporal scalability, and combinations of transient dynamic data and persistent downloaded data. This approach can lower bandwidth of mixed media, offer tradeoffs in quality versus update for specific terminals, and foster varied distribution methods for content that exploit spatial and temporal coherence over buses and networks. MPEG-4 responds to trends at home and work to move beyond the paradigm of audio/video as a passive experience to more flexible A/V objects which combine audio/video with synthetic 2D/3D graphics and audio.

A Trainingless WiFi Fingerprint Positioning Approach Over Mobile Devices

Indoor localization of targets by using electromagnetic waves has attracted a lot of attention in the last few years. Thanks to the wide availability of electromagnetic sources deployed for various applications (e.g., WiFi), nowadays it is possible to perform this task by using low-cost mobile devices, such as smartphones. To this end, in order to achieve high positioning accuracy and reduce the computational resources used in the position estimation, fingerprinting approaches are usually employed. However, in this case, a time-consuming training phase, where a great number of measurements must be performed, is needed. In this letter, a novel approach, where the training data are obtained by means of finite-difference time-domain (FDTD) simulations of the electromagnetic propagation in the considered scenario, is presented. The performances of the method are assessed by means of experimental results in a real scenario.

Gender-Driven Emotion Recognition Through Speech Signals For Ambient Intelligence Applications

This paper proposes a system that allows recognizing a persons emotional state starting from audio signal registrations. The provided solution is aimed at improving the interaction among humans and computers, thus allowing effective human-computer intelligent interaction. The system is able to recognize six emotions(anger, boredom, disgust, fear, happiness, and sadness) and the neutral state. This set of emotional states is widely used for emotion recognition purposes. It also distinguishes a single emotion versus all the other possible ones, as proven in the proposed numerical results. The system is composed of two subsystems: 1) gender recognition(GR) and 2) emotion recognition(ER). The experimental analysis shows the performance in terms of accuracy of the proposed ER system. The results highlight that the a priori knowledge of the speakers gender allows a performance increase. The obtained results show also that the features selection adoption assures a satisfying recognition rate and allows reducing the employed features. Future developments of the proposed solution may include the implementation of this system over mobile devices such as smartphones.

Smartphone-centric ambient assisted living platform for patients suffering from co-morbidities monitoring

Recently, patients suffering from a set of physical and mental limitations, called co-morbidities, are often treated at home. In this environment, modern communication systems represent a great support to implement Ambient Assisted Living platforms aimed at monitoring patients at home because they enable the seamless integration of heterogeneous sensing units, medical devices, and ubiquitous access to data. This article describes a specific smartphone-centric architecture where smartphones are employed not only as hubs of the health information but also as sensing, processing, and transmitting devices. Smartphones have both short-range (Bluetooth and WiFi employed for local information exchange) and long-range (GPRS, 3G/4G, and WiFi employed as Internet access) communication capabilities; information processing capabilities offered by modern platforms often equipped with different CPUs and with flexible and efficient software; and sensing capabilities implemented through sensors embedded into smartphones such as GPS receivers, accelerometers, microphones, and radio interfaces or through external sensors added to smartphones by cables or connected through local radio interfaces. The specific case of co-morbidities considered in this article implies the necessity to acquire a heterogeneous set of data from patients and from their environment. For this reason this article highlights the information processing capabilities of the introduced smartphone-centric platform. Audio, localization, and movement information processing have been evidenced as well as the specific implementations of these capabilities and their performance.

Proximity classification for mobile devices using wi-fi environment similarity

This paper describes an algorithm to compute lists of people and devices that are physically nearby to a mobile user based on the analysis of signals from existing wireless networks. The system evaluates proximity by classifying the degree of similarity of the Wi-Fi scan data through a statistical Gaussian Mixture Model. It recognizes when the devices are in the same area, and, in this case, it distinguishes three proximity levels: High (e.g. same room), Medium (e.g. same floor) and Low (e.g. same building). The algorithm can be deployed on a remote server that receives Wi-Fi scanning data (including MAC addresses and signal strength) from mobile devices. The server estimates proximity by extracting a set of features from each received pair of Wi-Fi data, feeding them to the GMM model and selecting the category with greatest probability. The method presented in the paper does not require calibration and leverages on existing Wi-Fi signals, while obtaining a percentage of correct discrimination among three levels near to 90%.

Smart probabilistic fingerprinting for WiFi-based indoor positioning with mobile devices

Different positioning schemes are based on the probability p ( o | l ) to have an observation vector o at a Reference Point (RP) l , based on Gaussian probabilities. This paper presents an approach to speed-up the p ( o | l ) computation without any approximation. The consequent positioning scheme is called Smart P-FP. The comparison between Traditional (without any p ( o | l ) acceleration) and Smart P-FP is performed over different smartphones. The saved energy is about 90% for a large number of Access Points (APs) but is significant even with few APs: more than 86% with 3 APs. The proposed p ( o | l ) computation is beneficial to any p ( o | l ) -based positioning scheme.

An efficient use of MPEG-4 FAP interpolation for facial animation at 70 bits/frame

An efficient algorithm is proposed to exploit the facial animation parameter (FAP) interpolation modality specified by the MPEG-4 standard in order to allow very low bit-rate transmission of the animation parameters. The proposed algorithm is based on a comprehensive analysis of the cross-correlation properties that characterize FAPs, which is here reported and discussed extensively. Based on this analysis, a subset of ten almost independent FAPs has been selected from the full set of 66 low-level FAPs to be transmitted and used at the decoder to interpolate the remaining ones. The performance achievable through the proposed algorithm have been evaluated objectively by means of conventional PSNR measures and compared to an alternative solution based on the increase of the quantization scale factor used for FAP encoding. The subjective evaluation and comparison of the results has also been made possible by uploading mpg movies on a freely accessible Web site. Experimental results demonstrate that the proposed FAP interpolation algorithm allows efficient parameter encoding at around 70 bits/frame or, in other words, at less than 2 kbits/s for smooth synthetic video at 25 frames/s.

Object-oriented scene modeling for interpersonal video communication at very low bit-rate☆

Abstract This paper describes a new approach to very low bit-rate interpersonal visual communication based on a suitable scene model, i.e. a flexible structure adapted to the specific characteristics of the speakers face. The face model is dynamically adapted to time-varying facial expressions by means of few parameters, estimated from the analysis of the real image sequence, which are used to apply knowledge-based deformation rules on a simplified muscle structure. Facial muscles are distributed in correspondence to the primary facial features and can be activated through the direct stimulation of each individual fiber or, indirectly, by interaction with adjacent stimulated fibers. The analysis algorithms performed at the transmitter to estimate the model parameters are based on feature-oriented operators aimed at segmenting the real incoming frames and at the extraction of the primary facial descriptors. The analysis/synthesis algorithms have been developed on a Silicon Graphics workstation and have been tested on various ‘head-and-shoulder’ sequences: the obtained results are very promising for applications both in videophone coding and in picture animation, where the facial expressions of a synthetic actor is reproduced according to the parameters extracted from a real speaking face.

Energy efficient WiFi-based fingerprinting for indoor positioning with smartphones

The paper presents an energy efficient WiFi-based indoor positioning algorithm, based on the probabilistic fingerprinting method, suited to be used over smartphone platforms. The work proposes a simple algebraic approach aimed at reducing the computational and energy loads of the probabilistic fingerprinting, which is employed to carry out the position of a smartphone on the basis of the captured WiFi Access Points signal strengths in an indoor area. The presented solution does not apply any kind of approximation with respect to the traditional approach, so avoiding accuracy detriment. The idea is to factoring out the parts of the probabilistic fingerprint formulae that can be computed a-priori, so reducing the computational burden of the positioning process. The paper also highlights the effectiveness of the proposed solution by evaluating the energy saved in comparison with the traditional approach. The obtained results, collected by testing three different smartphones, show that our approach allows saving a significant quantity of energy so increasing the smartphones battery lifetime.