Nokia

About: Nokia is a company organization based out in Espoo, Finland. It is known for research contribution in the topics: Signal & Mobile station. The organization has 16625 authors who have published 28347 publications receiving 695725 citations. The organization is also known as: Nokia Oyj & Oy Nokia Ab.

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.

Quality of service support in IEEE 802.16 networks

Abstract: During the last few years, users ail over the world have become more and more accustomed to the availability of broadband access. This has boosted the use of a wide variety both of established and recent multimedia applications. However, there are cases where it is too expensive for network providers to serve a community of users. This is typically the case in rural and suburban areas, where there is slow deployment (or no deployment at all) of traditional wired technologies for broadband access (e.g., cable modems, xDSL). In those cases, the most promising opportunity rests with broadband wireless access technologies, such as the IEEE 802.16, also known as WiMAX. One of the features of the MAC layer of 802.16 is that it is designed to differentiate service among traffic categories with different multimedia requirements. This article focuses on mechanisms that are available in an 802.16 system to support quality of service (QoS) and whose effectiveness is evaluated through simulation

Audio-based context recognition

Abstract: The aim of this paper is to investigate the feasibility of an audio-based context recognition system. Here, context recognition refers to the automatic classification of the context or an environment around a device. A system is developed and compared to the accuracy of human listeners in the same task. Particular emphasis is placed on the computational complexity of the methods, since the application is of particular interest in resource-constrained portable devices. Simplistic low-dimensional feature vectors are evaluated against more standard spectral features. Using discriminative training, competitive recognition accuracies are achieved with very low-order hidden Markov models (1-3 Gaussian components). Slight improvement in recognition accuracy is observed when linear data-driven feature transformations are applied to mel-cepstral features. The recognition rate of the system as a function of the test sequence length appears to converge only after about 30 to 60 s. Some degree of accuracy can be achieved even with less than 1-s test sequence lengths. The average reaction time of the human listeners was 14 s, i.e., somewhat smaller, but of the same order as that of the system. The average recognition accuracy of the system was 58% against 69%, obtained in the listening tests in recognizing between 24 everyday contexts. The accuracies in recognizing six high-level classes were 82% for the system and 88% for the subjects.

Accuracy measures for evaluating computer pointing devices

Abstract: In view of the difficulties in evaluating computer pointing devices across different tasks within dynamic and complex systems, new performance measures are needed. This paper proposes seven new accuracy measures to elicit (sometimes subtle) differences among devices in precision pointing tasks. The measures are target re-entry, task axis crossing, movement direction change, orthogonal direction change, movement variability, movement error, and movement offset. Unlike movement time, error rate, and throughput, which are based on a single measurement per trial, the new measures capture aspects of movement behaviour during a trial. The theoretical basis and computational techniques for the measures are described, with examples given. An evaluation with four pointing devices was conducted to validate the measures. A causal relationship to pointing device efficiency (viz. throughput) was found, as was an ability to discriminate among devices in situations where differences did not otherwise appear. Implications for pointing device research are discussed.