Showing papers by "Nokia published in 2011"

Resource Sharing Optimization for Device-to-Device Communication Underlaying Cellular Networks

Abstract: We consider Device-to-Device (D2D) communication underlaying cellular networks to improve local services. The system aims to optimize the throughput over the shared resources while fulfilling prioritized cellular service constraints. Optimum resource allocation and power control between the cellular and D2D connections that share the same resources are analyzed for different resource sharing modes. Optimality is discussed under practical constraints such as minimum and maximum spectral efficiency restrictions, and maximum transmit power or energy limitation. It is found that in most of the considered cases, optimum power control and resource allocation for the considered resource sharing modes can either be solved in closed form or searched from a finite set. The performance of the D2D underlay system is evaluated in both a single-cell scenario, and a Manhattan grid environment with multiple WINNER II A1 office buildings. The results show that by proper resource management, D2D communication can effectively improve the total throughput without generating harmful interference to cellular networks.

Mechanically Durable Superhydrophobic Surfaces

Abstract: Development of durable non-wetting surfaces is hindered by the fragility of the microscopic roughness features that are necessary for superhydrophobicity. Mechanical wear on superhydrophobic surfaces usually shows as increased sticking of water, leading to loss of non-wettability. Increased wear resistance has been demonstrated by exploiting hierarchical roughness where nanoscale roughness is protected to some degree by large scale features, and avoiding the use of hydrophilic bulk materials is shown to help prevent the formation of hydrophilic defects as a result of wear. Additionally, self-healing hydrophobic layers and roughness patterns have been suggested and demonstrated. Nevertheless, mechanical contact not only causes damage to roughness patterns but also surface contamination, which shortens the lifetime of superhydrophobic surfaces in spite of the self-cleaning effect. The use of photocatalytic effect and reduced electric resistance have been suggested to prevent the accumulation of surface contaminants. Resistance to organic contaminants is more challenging, however, oleophobic surface patterns which are non-wetting to organic liquids have been demonstrated. While the fragility of superhydrophobic surfaces currently limits their applicability, development of mechanically durable surfaces will enable a wide range of new applications in the future.

Computer Vision Using Local Binary Patterns

Abstract: The recent emergence of Local Binary Patterns (LBP) has led to significant progress in applying texture methods to various computer vision problems and applications. The focus of this research has broadened from 2D textures to 3D textures and spatiotemporal (dynamic) textures. Also, where texture was once utilized for applications such as remote sensing, industrial inspection and biomedical image analysis, the introduction of LBP-based approaches have provided outstanding results in problems relating to face and activity analysis, with future scope for face and facial expression recognition, biometrics, visual surveillance and video analysis. Computer Vision Using Local Binary Patterns provides a detailed description of the LBP methods and their variants both in spatial and spatiotemporal domains. This comprehensive reference also provides an excellent overview as to how texture methods can be utilized for solving different kinds of computer vision and image analysis problems. Source codes of the basic LBP algorithms, demonstrations, some databases and a comprehensive LBP bibliography can be found from an accompanying web site. Topics include: local binary patterns and their variants in spatial and spatiotemporal domains, texture classification and segmentation, description of interest regions, applications in image retrieval and 3D recognition - Recognition and segmentation of dynamic textures, background subtraction, recognition of actions, face analysis using still images and image sequences, visual speech recognition and LBP in various applications. Written by pioneers of LBP, this book is an essential resource for researchers, professional engineers and graduate students in computer vision, image analysis and pattern recognition. The book will also be of interest to all those who work with specific applications of machine vision.

A Framework for Hand Gesture Recognition Based on Accelerometer and EMG Sensors

Abstract: This paper presents a framework for hand gesture recognition based on the information fusion of a three-axis accelerometer (ACC) and multichannel electromyography (EMG) sensors. In our framework, the start and end points of meaningful gesture segments are detected automatically by the intensity of the EMG signals. A decision tree and multistream hidden Markov models are utilized as decision-level fusion to get the final results. For sign language recognition (SLR), experimental results on the classification of 72 Chinese Sign Language (CSL) words demonstrate the complementary functionality of the ACC and EMG sensors and the effectiveness of our framework. Additionally, the recognition of 40 CSL sentences is implemented to evaluate our framework for continuous SLR. For gesture-based control, a real-time interactive system is built as a virtual Rubik's cube game using 18 kinds of hand gestures as control commands. While ten subjects play the game, the performance is also examined in user-specific and user-independent classification. Our proposed framework facilitates intelligent and natural control in gesture-based interaction.

Discriminative Learning of Local Image Descriptors

Abstract: In this paper, we explore methods for learning local image descriptors from training data. We describe a set of building blocks for constructing descriptors which can be combined together and jointly optimized so as to minimize the error of a nearest-neighbor classifier. We consider both linear and nonlinear transforms with dimensionality reduction, and make use of discriminant learning techniques such as Linear Discriminant Analysis (LDA) and Powell minimization to solve for the parameters. Using these techniques, we obtain descriptors that exceed state-of-the-art performance with low dimensionality. In addition to new experiments and recommendations for descriptor learning, we are also making available a new and realistic ground truth data set based on multiview stereo data.

City-scale landmark identification on mobile devices

Abstract: With recent advances in mobile computing, the demand for visual localization or landmark identification on mobile devices is gaining interest. We advance the state of the art in this area by fusing two popular representations of street-level image data — facade-aligned and viewpoint-aligned — and show that they contain complementary information that can be exploited to significantly improve the recall rates on the city scale. We also improve feature detection in low contrast parts of the street-level data, and discuss how to incorporate priors on a user's position (e.g. given by noisy GPS readings or network cells), which previous approaches often ignore. Finally, and maybe most importantly, we present our results according to a carefully designed, repeatable evaluation scheme and make publicly available a set of 1.7 million images with ground truth labels, geotags, and calibration data, as well as a difficult set of cell phone query images. We provide these resources as a benchmark to facilitate further research in the area.

Rate adaptation for adaptive HTTP streaming

Abstract: Recently, HTTP has been widely used for the delivery of real-time multimedia content over the Internet, such as in video streaming applications. To combat the varying network resources of the Internet, rate adaptation is used to adapt the transmission rate to the varying network capacity. A key research problem of rate adaptation is to identify network congestion early enough and to probe the spare network capacity. In adaptive HTTP streaming, this problem becomes challenging because of the difficulties in differentiating between the short-term throughput variations, incurred by the TCP congestion control, and the throughput changes due to more persistent bandwidth changes.In this paper, we propose a novel rate adaptation algorithm for adaptive HTTP streaming that detects bandwidth changes using a smoothed HTTP throughput measured based on the segment fetch time (SFT). The smoothed HTTP throughput instead of the instantaneous TCP transmission rate is used to determine if the bitrate of the current media matches the end-to-end network bandwidth capacity. Based on the smoothed throughput measurement, this paper presents a receiver-driven rate adaptation method for HTTP/TCP streaming that deploys a step-wise increase/ aggressive decrease method to switch up/down between the different representations of the content that are encoded at different bitrates. Our rate adaptation method does not require any transport layer information such as round trip time (RTT) and packet loss rates which are available at the TCP layer. Simulation results show that the proposed rate adaptation algorithm quickly adapts to match the end-to-end network capacity and also effectively controls buffer underflow and overflow.

Robust text detection in natural images with edge-enhanced Maximally Stable Extremal Regions

Abstract: Detecting text in natural images is an important prerequisite. In this paper, we propose a novel text detection algorithm, which employs edge-enhanced Maximally Stable Extremal Regions as basic letter candidates. These candidates are then filtered using geometric and stroke width information to exclude non-text objects. Letters are paired to identify text lines, which are subsequently separated into words. We evaluate our system using the ICDAR competition dataset and our mobile document database. The experimental results demonstrate the excellent performance of the proposed method.

Real-time routing with OpenStreetMap data

Abstract: Routing services on the web and on hand-held devices have become ubiquitous in the past couple of years. Websites like Bing or Google Maps allow users to find routes between arbitrary locations comfortably in no time. Likewise onboard navigation units belong to the off-the-shelf equipment of virtually any new car.The amount of volunteered spatial data of the OpenStreetMap project has increased rapidly in the past five years. In many areas, the data quality already matches that of commercial map data, if not outright surpass it.We demonstrate both a server and a hand-held device based implementation working with OpenStreetMap data. Both applications provide real-time and exact shortest path computation on continental sized networks with millions of street segments.We also demonstrate sophisticated real-time features like draggable routes and round-trip planning.

Survey on Energy Consumption Entities on the Smartphone Platform

Abstract: The full degree of freedom in mobile systems heavily depends on the energy provided by the mobile phone's batteries. Their capacity is in general limited and for sure not keeping pace as the mobile devices are crammed up with new functionalities. The discrepancy of Moore's law, offering twice the processing power at least each second year, and the development in batteries, which did not even double over the last decade, makes a shift in researchers' way of designing networks, protocols, and the mobile device itself. The bottleneck to take care of in the design process of mobile systems is not only the wireless data rate, but even more the energy limitation as the customers ask for new energy-hungry services, e.g., requiring faster connections or even multiple air interfaces, and longer standby or operational times of their mobile devices at the same time. In this survey, the energy consuming entities of a mobile device such as wireless air interfaces, display, mp3 player and others are measured and compared. The presented measurement results allow the reader to understand what the energy hungry parts of a mobile device are and use those findings for the design of future mobile protocols and applications. All results presented in this work and further results are made public on our web page [2].

Three-Dimensional Displays: A Review and Applications Analysis

Abstract: S. Benton published a definitive taxonomy of the first one hundred and seventy years of 3D displays covering the field up to the year 2000. In this article we review how display technologies have advanced in the last ten years and update Benton's taxonomy to include the latest additions. Our aim is to produce a display taxonomy suitable for content producers highlighting which displays have common requirements for image delivery. We also analyze key technical characteristics of 3D displays and use these characteristics to suggest the future applications for each category of display.

Agile methods rapidly replacing traditional methods at Nokia: A survey of opinions on agile transformation

Abstract: Context: Many organizations have started to deploy agile methods, but so far there exist only a few studies on organization-wide transformations. Are agile methods here to stay? Some claim that agile software development methods are in the mainstream adoption phase in the software industry, while others hope that those are a passing fad. The assumption here is that if agile would not provide real improvement, adopters would be eager at first but turn pessimistic after putting it into practice. Objective: Despite the growing amount of anecdotal evidence on the success of agile methods across a wide range of different real-life development settings, scientific studies remain scarce. Even less is known about the perception of the impacts of agile transformation when it is deployed in a very large software development environment, and whether agile methods are here to stay. This study aims to fill that gap by providing evidence from a large-scale agile transformation within Nokia. While we have yet to confirm these findings with solid quantitative data, we believe that the perception of the impacts already pinpoints the direction of the impacts of large-scale agile transformation. Method: The data were collected using a questionnaire. The population of the study contains more than 1000 respondents in seven different countries in Europe, North America, and Asia. Results: The results reveal that most respondents agree on all accounts with the generally claimed benefits of agile methods. These benefits include higher satisfaction, a feeling of effectiveness, increased quality and transparency, increased autonomy and happiness, and earlier detection of defects. Finally, 60% of respondents would not like to return to the old way of working. Conclusion: While the perception of the impact of agile methods is predominantly positive, several challenge areas were discovered. However, based on this study, agile methods are here to stay.

A Stepwise Nicolson–Ross–Weir-Based Material Parameter Extraction Method

Abstract: Approaches of automated evaluation of electromagnetic material parameters have received a lot of attention in the literature. Among others, one method is to retrieve the material parameters from the reflection and transmission measurements of the sample material. Compared to other methods, this is a rather wideband method, but suffers from an intrinsic limitation related to the electrical thickness of the measured material. In this letter, we propose a novel way to overcome this limitation. Although being based on the classical Nicolson-Ross-Weir (NRW) technique, the proposed extraction technique does not involve any branch seeking and is therefore capable of extracting material parameters from samples thicker than λ/2, a measure that would otherwise cause problems in the NRW extraction technique. The proposed derivative of the NRW extraction technique is then used to study the effect of thermal noise on the extracted material parameters.

Nenya: subtle and eyes-free mobile input with a magnetically-tracked finger ring

Abstract: We present Nenya, a new input device in the shape of a finger ring. Nenya provides an input mechanism that is always available, fast to access, and allows analog input, while remaining socially acceptable by being embodied in commonly worn items. Users make selections by twisting the ring and "click" by sliding it along the finger. The ring - the size of a regular wedding band - is magnetic, and is tracked by a wrist-worn sensor. Nenya's tiny size, eyes-free usability, and physical form indistinguishable from a regular ring make its use subtle and socially acceptable. We present two user studies (one- and two-handed) in which we studied sighted and eyes-free use, finding that even with no visual feedback users were able to select from eight targets.

HMM-Based Speech Synthesis Utilizing Glottal Inverse Filtering

Abstract: This paper describes an hidden Markov model (HMM)-based speech synthesizer that utilizes glottal inverse filtering for generating natural sounding synthetic speech. In the proposed method, speech is first decomposed into the glottal source signal and the model of the vocal tract filter through glottal inverse filtering, and thus parametrized into excitation and spectral features. The source and filter features are modeled individually in the framework of HMM and generated in the synthesis stage according to the text input. The glottal excitation is synthesized through interpolating and concatenating natural glottal flow pulses, and the excitation signal is further modified according to the spectrum of the desired voice source characteristics. Speech is synthesized by filtering the reconstructed source signal with the vocal tract filter. Experiments show that the proposed system is capable of generating natural sounding speech, and the quality is clearly better compared to two HMM-based speech synthesis systems based on widely used vocoder techniques.

IEEE 802.11ac: Enhancements for very high throughput WLANs

Abstract: The IEEE 802.11ac is an emerging very high throughput (VHT) WLAN standard that could achieve PHY data rates of close to 7 Gbps for the 5 GHz band. In this paper, we introduce the key mandatory and optional PHY features, as well as the MAC enhancements of 802.11ac over the existing 802.11n standard in the evolution towards higher data rates. Through numerical analysis and simulations, we compare the MAC performance between 802.11ac and 802.11n over three different frame aggregation mechanisms, viz., aggregate MAC service data unit (A-MSDU), aggregate MAC protocol data unit (A-MPDU), and hybrid A-MSDU/A-MPDU aggregation. Our results indicate that 802.11ac with a configuration of 80MHz and single (two) spatial stream(s) outperforms 802.11n with a configuration of 40 MHz and two spatial streams in terms of maximum throughput by 28% (84%). In addition, we demonstrate that hybrid A-MSDU/A-MPDU aggregation yields the best performance for both 802.11n and 802.11ac devices, and its improvement is a function of the maximum A-MSDU size.

Method and apparatus for correlating and navigating between a live image and a prerecorded panoramic image

Abstract: An approach is provided for correlating and navigating between a live camera image and a prerecorded panoramic image A mapping and augmented reality application correlates at least one live image with a prerecorded panoramic image, when a first location of a device used to capture the at least one live image substantially matches or falls within a predetermined proximity of a second location of a device used to capture the panoramic prerecorded image The mapping and augmented reality application causes, at least in part, alternating of the at least one live image and the prerecorded panoramic image in a presentation on a screen of the device capturing the at least one live image

Who's Who with Big-Five: Analyzing and Classifying Personality Traits with Smartphones

Abstract: In this paper, we investigate the relationship between behavioral characteristics derived from rich smart phone data and self-reported personality traits. Our data stems from smart phones of a set of 83 individuals collected over a continuous period of 8 months. From the analysis, we show that aggregated features obtained from smart phone usage data can be indicators of the Big-Five personality traits. Additionally, we develop an automatic method to infer the personality type of a user based on cell phone usage using supervised learning. We show that our method performs significantly above chance and up to 75.9% accuracy. To our knowledge, this constitutes the first study on the analysis and classification of personality traits using smartphone data.

SenGuard: Passive user identification on smartphones using multiple sensors

Abstract: User identification and access control have become a high demand feature on mobile devices because those devices are wildly used by employees in corporations and government agencies for business and store increasing amount of sensitive data. This paper describes SenGuard, a user identification framework that enables continuous and implicit user identification service for smartphone. Different from traditional active user authentication and access control, SenGuard leverages availability of multiple sensors on today's smartphones and passively use sensor inputs as sources of user authentication. It extracts sensor modality dependent user identification features from captured sensor data and performs user identification at background. SenGuard invokes active user authentication when there is a mounting evidence that the phone user has changed. In addition, SenGuard uses a novel virtualization based system architecture as a safeguard to prevent subversion of the background user identification mechanism by moving it into a privileged virtual domain. An initial prototype of SenGuard was created using four sensor modalities including, voice, location, multitouch, and locomotion. Preliminary empirical studies with a set of users indicate that those four modalities are suited as data sources for implicit mobile user identification.

Smartphone usage in the wild: a large-scale analysis of applications and context

Abstract: This paper presents a large-scale analysis of contextualized smartphone usage in real life. We introduce two contextual variables that condition the use of smartphone applications, namely places and social context. Our study shows strong dependencies between phone usage and the two contextual cues, which are automatically extracted based on multiple built-in sensors available on the phone. By analyzing continuous data collected on a set of 77 participants from a European country over 9 months of actual usage, our framework automatically reveals key patterns of phone application usage that would traditionally be obtained through manual logging or questionnaire. Our findings contribute to the large-scale understanding of applications and context, bringing out design implications for interfaces on smartphones.

Local Binary Patterns for Still Images

Abstract: This chapter provides an in-depth description of the LBP operator in spatial image domain. The generic LBP operator, and its rotation-invariant and multiscale versions are introduced. The use of complementary contrast information is also discussed. The success of LBP methods in various computer vision problems and applications has inspired much new research on different variants. The basic LBP has also some problems that need to be addressed. Therefore, several extensions and modifications of LBP have been proposed to increase its robustness and discriminative power.

Pass-them-around: collaborative use of mobile phones for photo sharing

Abstract: In this paper we explore shared collocated interactions with mobile phones. We introduce a phone-based application that allows a small group of collocated people to share photos using the metaphor of passing paper photos around. The prototype encourages people to share their devices and use them interchangeably while discussing photos face-to-face. The prototype supports ad-hoc photo sharing in different contexts by taking into account the spatial arrangement of users around a table, measured with sensors embedded in their mobile phones. Our evaluations show that people are willing to share and connect their mobile phones to engage in collaborative interactions. Participants were able to easily share their collections of photos using our proposed interaction techniques.

Measurements and fast power adjustments in D2D communications

Abstract: At a cluster head/first device there is received, from each of at least two other devices with which the cluster head has a respective wireless link, a quality indicator for the respective link observed by the respective other device. The cluster head compiles those received quality indicators into a compressed report, and sends the compressed report to a network entity. In a specific embodiment the cluster head also determines an additional quality indicator of each of those respective links observed by the cluster head by listening to a sounding reference signal sent by the respective other device to the network entity on a PUCCH. Those additional quality indicators are also compiled into the compressed report, as are further quality indicators received from the devices for D2D links between pairs of those other devices that exclude the cluster head. The compressed report can inform how many indicators are above/below a threshold.

Method and apparatus for providing content over multiple displays

Abstract: An approach is presented for providing content over multiple displays. A display manager causes, at least in part, presentation of a first content on a first display. The display manager then receives an input for activating one or more second displays. The display manager selects a second content based, at least in part, on the first content and the input, and causes, at least in part, presentation of the second content on the one o more second displays.

Implications of device diversity for organic localization

Abstract: Many indoor localization methods are based on the association of 802.11 wireless RF signals from wireless access points (WAPs) with location labels. An “organic” RF positioning system relies on regular users, not dedicated surveyors, to build the map of RF fingerprints to location labels. However, signal variation due to device heterogeneity may degrade localization performance. We analyze the diversity of those signal characteristics pertinent to indoor localization — signal strength and AP detection — as measured by a variety of 802.11 devices. We first analyze signal strength diversity, and show that pairwise linear transformation alone does not solve the problem. We propose kernel estimation with a wide kernel width to reduce the difference in probability estimates. We also investigate diversity in access point detection. We demonstrate that localization performance may degrade significantly when AP detection rate is used as a feature for localization, and correlate the loss of performance to a device dissimilarity measure captured by Kullback-Leibler divergence. Based on this analysis, we show that using only signal strength, without incorporating negative evidence, achieves good localization performance when devices are heterogeneous.

Dynamic Coverage of Mobile Sensor Networks

Abstract: In this paper we study the dynamic aspects of the coverage of a mobile sensor network resulting from continuous movement of sensors. As sensors move around, initially uncovered locations are likely to be covered at a later time. A larger area is covered as time continues, and intruders that might never be detected in a stationary sensor network can now be detected by moving sensors. However, this improvement in coverage is achieved at the cost that a location is covered only part of the time, alternating between covered and not covered. We characterize area coverage at specific time instants and during time intervals, as well as the time durations that a location is covered and uncovered. We further characterize the time it takes to detect a randomly located intruder. For mobile intruders, we take a game theoretic approach and derive optimal mobility strategies for both sensors and intruders. Our results show that sensor mobility brings about unique dynamic coverage properties not present in a stationary sensor network, and that mobility can be exploited to compensate for the lack of sensors to improve coverage.

Methods and apparatuses for facilitating task switching

Abstract: Methods and apparatuses are provided for facilitating task switching. A method may include detecting activation of a second display on a multi-display computing apparatus including a first and second display. The first display may be in an active state prior to activation of the second display. The method may further include causing a task selection interface to be displayed in response to the detected activation. Corresponding apparatuses are also provided.

Method, apparatus and computer program product for creating a wireless docking group

Abstract: Method, apparatus, and computer program product embodiments are disclosed to enable simplified configuring of a wireless docking group for wireless devices by allowing a wireless device to communicate its capabilities and characteristics of one or more wireless devices within a wireless docking group, using a new Wireless Docking Protocol, to a wireless docking station that will use that information and the Wireless Docking Protocol to define an optimal set of connections for wireless devices in the wireless docking group.