Modelling on mobile devices

Software and Systems Modeling - Modelling is central to many disciplines in engineering and the natural and social sciences. A wide variety of modelling languages and tools have been proposed along...     

Managing context information in mobile devices

We present a uniform mobile terminal software framework that provides systematic methods for acquiring and processing useful context information from a user's surroundings and giving it to applications. The framework simplifies the development of context-aware mobile applications by managing raw context information gained from multiple sources and enabling higher-level context abstractions.     

Speeding-up homography estimation in mobile devices

A critical problem faced by computer vision on mobile devices is reducing the computational cost of algorithms and avoiding visual stalls. In this paper, we introduce a procedure for reducing the number of samples required for fitting a homography to a set of noisy correspondences using a random sampling method. This is achieved by means of a geometric constraint that detects invalid minimal sets. In the experiments conducted, we show that this constraint not only reduces the number of random samples at a negligible computational cost but also balances the processor workload over time preventing visual stalls. In extreme situations of very large outlier proportion and noise level, it reduces in about one order of magnitude the number of required random samples.     

An economics-based negotiation scheme among mobile devices in mobile grid

In this paper, we propose an economics-based distributed negotiation scheme among mobile devices in mobile grid. In our model, there are energy negotiation and transactions between buyer devices and seller devices. Dynamic allocation of energy resources in mobile grid is performed through online transactions within markets. Mobile devices can be sellers and buyers that use optimization algorithms to maximize predefined utility functions during their transactions. Seller device agents sell the underlying energy resources of the mobile device. Buyer device agent makes buying decisions within the budget constraints to acquire energy resources. An economics-based negotiation algorithm among mobile devices is proposed. The proposed algorithm decomposes mobile grid system optimization problem into a sequence of two sub-problems. In the simulation, the performance evaluation of economics-based negotiation algorithm is evaluated.     

Speech recognition for mobile devices

This article presents an overview of different approaches for providing automatic speech recognition (ASR) technology to mobile users. Three principal system architectures with respect to the employment of a wireless communication link are analyzed: Embedded Speech Recognition Systems, Network Speech Recognition (NSR) and Distributed Speech Recognition (DSR). An overview of the solutions having been standardized so far as well as a critical analysis of the latest developments in the field of speech recognition in mobile environments is given. Open issues, pros and cons of the different methodologies and techniques are highlighted. Special emphasis is placed on the constraints and limitations ASR applications are confronted with under different architectures.     

Visualizing information on mobile devices

Visualization can make a wide range of mobile applications more intuitive and productive. The mobility context and technical limitations such as small screen size make it impossible to simply port visualization applications from desktop computers to mobile devices, but researchers are starting to address these challenges. From a purely technical point of view, building more sophisticated mobile visualizations become easier due to new, possibly standard, software APIs such as OpenGLES and increasingly powerful devices. Although ongoing improvements would not eliminate most device limitations or alter the mobility context, they make it easier to create and experiment with alternative approaches.     

支持移动设备接入Gnutella网络的代理架构研究

针对当前移动设备无法加入Gnutella网络实现文件共享网络的现状,提出一种移动代理Gnutella网络架构的设计方案。利用移动代理作为移动设备的代理加入Gnutella网络,帮助移动设备实现文件的共享功能。架构能有效地减少移动设备的信息流量,并支持移动设备在Gnutella网络中实现可移动性。     

High-performance code optimizations for mobile devices

The Journal of Supercomputing - Mobile devices have seen their performance increased in latest years due to improvements on System on Chip technologies. These shared memory systems now integrate...     

Automatic form filling on mobile devices

Filling out forms for web based services on mobile devices is a very time consuming and frustrating task for users because of the limited text input capabilities. This is a critical bottleneck to obtaining a wide acceptance of such services, especially mobile commerce that often requires filling user data. We developed an architecture based on a local proxy on a mobile device and a lightweight algorithm for a comprehensive analysis of forms, which leads to the most probable user data to be filled in, driven by an initial rule set [Chie Noda, John Hamard, Enrico Rukzio, Alexander De Luca, Method and Apparatus for Automatic Form Filling on Mobile Devices, Patent. Publication number EP1777629, Publication date 2007-04-25]. We further discuss our implementation and the evaluation results for the algorithm as well as the usability of the prototype.     

Flexible point-based rendering on mobile devices

We have seen the growing deployment of ubiquitous computing devices and the proliferation of complex virtual environments. As demand for detailed and high-quality geometric models increases, typical scene size (often including scanned 3D objects) easily reaches millions of geometric primitives. Traditionally, vertices and polygons (faces) represent 3D objects. These representations, coupled with the traditional rendering pipeline, don't adequately support display of complex scenes on different types of platforms with heterogeneous rendering capabilities. To accommodate these constraints, we use a packed hierarchical point-based representation for rendering. Point-based rendering offers a simple-to-use level-of-detail mechanism in which we can adapt the number of points rendered to the underlying object's screen size. Our work strives for flexible rendering - that is, rendering only the interior hierarchy nodes as representatives of the subtree. In particular, we avoid traversal of the entire hierarchy and reconstruction of model attributes (such as normals and color information) for interior nodes because both operations can be prohibitively expensive. Flexible rendering also lets us traverse the hierarchy in a specific order, resulting in a fast, one-pass shadow-mapping algorithm.     

Super-resolution image reconstruction for mobile devices

With advanced mobile devices, the mobile applications of the high-definition display attract a lot of attentions nowadays. The existing image super-resolution methods are computationally inefficient for the high-definition display on the mobile devices. In this paper, we point out that the above critical issue deteriorates the display quality of the high-definition mobile devices. We propose an efficient and effective algorithm to reconstruct the high-resolution images for the mobile devices. Our algorithm outperforms previous approaches in not only smaller running time but also the higher quality of the super-resolution image reconstruction for the mobile devices.     

Real-time facial animation on mobile devices

We present a performance-based facial animation system capable of running on mobile devices at real-time frame rates. A key component of our system is a novel regression algorithm that accurately infers the facial motion parameters from 2D video frames of an ordinary web camera. Compared with the state-of-the-art facial shape regression algorithm [1], which takes a two-step procedure to track facial animations (i.e., first regressing the 3D positions of facial landmarks, and then computing the head poses and expression coefficients), we directly regress the head poses and expression coefficients. This one-step approach greatly reduces the dimension of the regression target and significantly improves the tracking performance while preserving the tracking accuracy. We further propose to collect the training images of the user under different lighting environments, and make use of the data to learn a user-specific regressor, which can robustly handle lighting changes that frequently occur when using mobile devices.     

Energy-aware resource sharing with mobile devices

Ad hoc sharing of resources by offering remote services through an appropriate infrastructure enables new applications for mobile devices. However, the willingness of device owners to contribute resources to such applications remains low as long as they cannot control the amount of energy spent in sharing. In this paper, we present a framework for energy-aware resource sharing among mobile devices of various kinds that comprises (1) energy-aware strategies for selecting remote service providers and (2) a generic energy estimator for forecasting and accounting the energy consumption of a remote service call. To illustrate the benefit of (1), we show by simulation that the battery lifetime of devices running the framework can be extended up to 40% by service selection strategies that take into account the energy cost of a requested service compared to energy-unaware (random) service selection. For providing the energy-related input for service selection, we present (2) a generic estimator that can be customized easily for different hardware-platforms by solving a linear equation system with coefficients derived from benchmark measurements. We present a prototype-based case study for three different platforms, the Nokia N810, the HTC Touch Cruise and the Samsung Galaxy S showing that for all of them the estimation error is below 10% for 90% of the service calls. Furthermore, measurements conducted with a prototype implementation of the resource sharing framework show that battery lifetime can in fact be extended by energy-aware service selection strategies.     

Interactive multi-frame reconstruction for mobile devices

The small size of handheld devices, their video capabilities and multiple cameras are under-exploited assets. Properly combined, the features can be used for creating novel applications that are ideal for pocket-sized devices, but may not be useful in laptop computers, such as interactively capturing and analyzing images on the fly. In this paper we consider building mosaic images of printed documents and natural scenes from low resolution video frames. High interactivity is provided by giving a real-time feedback on the video quality, while simultaneously guiding the user’s actions. In our contribution, we analyze and compare means to reach interactivity and performance with sensor signal processing and GPU assistance. The viability of the concept is demonstrated on a mobile phone. The achieved usability benefits suggest that combining interactive imaging and energy efficient high performance computing could enable new mobile applications and user interactions.     

Keystroke dynamics-based authentication for mobile devices

Recently, mobile devices are used in financial applications such as banking and stock trading. However, unlike desktops and notebook computers, a 4-digit personal identification number (PIN) is often adopted as the only security mechanism for mobile devices. Because of their limited length, PINs are vulnerable to shoulder surfing and systematic trial-and-error attacks. This paper reports the effectiveness of user authentication using keystroke dynamics-based authentication (KDA) on mobile devices. We found that a KDA system can be effective for mobile devices in terms of authentication accuracy. Use of artificial rhythms leads to even better authentication performance.     

Authentication in mobile devices through hand gesture recognition

This article proposes an innovative biometric technique based on the idea of authenticating a person on a mobile device by gesture recognition. To accomplish this aim, a user is prompted to be recognized by a gesture he/she performs moving his/her hand while holding a mobile device with an accelerometer embedded. As users are not able to repeat a gesture exactly in the air, an algorithm based on sequence alignment is developed to correct slight differences between repetitions of the same gesture. The robustness of this biometric technique has been studied within 2 different tests analyzing a database of 100 users with real falsifications. Equal Error Rates of 2.01 and 4.82% have been obtained in a zero-effort and an active impostor attack, respectively. A permanence evaluation is also presented from the analysis of the repetition of the gestures of 25 users in 10 sessions over a month. Furthermore, two different gesture databases have been developed: one made up of 100 genuine identifying 3-D hand gestures and 3 impostors trying to falsify each of them and another with 25 volunteers repeating their identifying 3-D hand gesture in 10 sessions over a month. These databases are the most extensive in published studies, to the best of our knowledge.     

移动设备的个性化推荐在上下文感知应用

个性化推荐对上下文感知系统具有广泛而重要应用,现在大多数个性化推荐系统很少考虑用户的认知风格.文中比较了场独立用户和场依赖用户在上下文感知环境中所存在的差异,提出一种基于用户认知风格的个性化推荐系统(CSBRS).通过CSBRS的实现例子,表明基于用户认知风格的个性化推荐有助于提高个性化推荐的质量.