Recent Trends and Techniques in Text Detection and Text Localization in a Natural Scene: A Survey

Text information extraction from natural scene images is a rising area of research. Since text in natural scene images generally carries valuable details, detecting and recognizing scene text has been deemed essential for a variety of advanced computer vision applications. There has been a lot of effort put into extracting text regions from scene text images in an effective and reliable manner. As most text recognition applications have high demand of robust algorithms for detecting and localizing texts from a given scene text image, so the researchers mainly focus on the two important stages text detection and text localization. This paper provides a review of various techniques of text detection and text localization

Effective Identity Management on Mobile Devices Using Multi-Sensor Measurements

Due to the dramatic increase in popularity of mobile devices in the past decade, sensitive user information is stored and accessed on these devices every day. Securing sensitive data stored and accessed from mobile devices, makes user-identity management a problem of paramount importance. The tension between security and usability renders the task of user-identity verification on mobile devices challenging. Meanwhile, an appropriate identity management approach is missing since most existing technologies for user-identity verification are either one-shot user verification or only work in restricted controlled environments. To solve the aforementioned problems, we investigated and sought approaches from the sensor data generated by human-mobile interactions. The data are collected from the on-board sensors, including voice data from microphone, acceleration data from accelerometer, angular acceleration data from gyroscope, magnetic force data from magnetometer, and multi-touch gesture input data from touchscreen. We studied the feasibility of extracting biometric and behaviour features from the on-board sensor data and how to efficiently employ the features extracted to perform user-identity verification on the smartphone device. Based on the experimental results of the single-sensor modalities, we further investigated how to integrate them with hardware such as fingerprint and Trust Zone to practically fulfill a usable identity management system for both local application and remote services control. User studies and on-device testing sessions were held for privacy and usability evaluation.Computer Science, Department o

Keskusteluavustimen kehittäminen kuulovammaisia varten automaattista puheentunnistusta käyttäen

Understanding and participating in conversations has been reported as one of the biggest challenges hearing impaired people face in their daily lives. These communication problems have been shown to have wide-ranging negative consequences, affecting their quality of life and the opportunities available to them in education and employment. A conversational assistance application was investigated to alleviate these problems. The application uses automatic speech recognition technology to provide real-time speech-to-text transcriptions to the user, with the goal of helping deaf and hard of hearing persons in conversational situations. To validate the method and investigate its usefulness, a prototype application was developed for testing purposes using open-source software. A user test was designed and performed with test participants representing the target user group. The results indicate that the Conversation Assistant method is valid, meaning it can help the hearing impaired to follow and participate in conversational situations. Speech recognition accuracy, especially in noisy environments, was identified as the primary target for further development for increased usefulness of the application. Conversely, recognition speed was deemed to be sufficient and already surpass the transcription speed of human transcribers.Keskustelupuheen ymmärtäminen ja keskusteluihin osallistuminen on raportoitu yhdeksi suurimmista haasteista, joita kuulovammaiset kohtaavat jokapäiväisessä elämässään. Näillä viestintäongelmilla on osoitettu olevan laaja-alaisia negatiivisia vaikutuksia, jotka heijastuvat elämänlaatuun ja heikentävät kuulovammaisten yhdenvertaisia osallistumismahdollisuuksia opiskeluun ja työelämään. Työssä kehitettiin ja arvioitiin apusovellusta keskustelupuheen ymmärtämisen ja keskusteluihin osallistumisen helpottamiseksi. Sovellus käyttää automaattista puheentunnistusta reaaliaikaiseen puheen tekstittämiseen kuuroja ja huonokuuloisia varten. Menetelmän toimivuuden vahvistamiseksi ja sen hyödyllisyyden tutkimiseksi siitä kehitettiin prototyyppisovellus käyttäjätestausta varten avointa lähdekoodia hyödyntäen. Testaamista varten suunniteltiin ja toteutettiin käyttäjäkoe sovelluksen kohderyhmää edustavilla koekäyttäjillä. Saadut tulokset viittaavat siihen, että työssä esitetty Keskusteluavustin on toimiva ja hyödyllinen apuväline huonokuuloisille ja kuuroille. Puheentunnistustarkkuus erityisesti meluisissa olosuhteissa osoittautui ensisijaiseksi kehityskohteeksi apusovelluksen hyödyllisyyden lisäämiseksi. Puheentunnistuksen nopeus arvioitiin puolestaan jo riittävän nopeaksi, ylittäen selkeästi kirjoitustulkkien kirjoitusnopeuden

Detecting head movement using gyroscope data collected via in-ear wearables

Abstract. Head movement is considered as an effective, natural, and simple method to determine the pointing towards an object. Head movement detection technology has significant potentiality in diverse field of applications and studies in this field verify such claim. The application includes fields like users interaction with computers, controlling many devices externally, power wheelchair operation, detecting drivers’ drowsiness while they drive, video surveillance system, and many more. Due to the diversity in application, the method of detecting head movement is also wide-ranging. A number of approaches such as acoustic-based, video-based, computer-vision based, inertial sensor data based head movement detection methods have been introduced by researchers over the years. In order to generate inertial sensor data, various types of wearables are available for example wrist band, smart watch, head-mounted device, and so on. For this thesis, eSense — a representative earable device — that has built-in inertial sensor to generate gyroscope data is employed. This eSense device is a True Wireless Stereo (TWS) earbud. It is augmented with some key equipment such as a 6-axis inertial motion unit, a microphone, and dual mode Bluetooth (Bluetooth Classic and Bluetooth Low Energy). Features are extracted from gyroscope data collected via eSense device. Subsequently, four machine learning models — Random Forest (RF), Support Vector Machine (SVM), Naïve Bayes, and Perceptron — are applied aiming to detect head movement. The performance of these models is evaluated by four different evaluation metrics such as Accuracy, Precision, Recall, and F1 score. Result shows that machine learning models that have been applied in this thesis are able to detect head movement. Comparing the performance of all these machine learning models, Random Forest performs better than others, it is able to detect head movement with approximately 77% accuracy. The accuracy rate of other three models such as Support Vector Machine, Naïve Bayes, and Perceptron is close to each other, where these models detect head movement with about 42%, 40%, and 39% accuracy, respectively. Besides, the result of other evaluation metrics like Precision, Recall, and F1 score verifies that using these machine learning models, different head direction such as left, right, or straight can be detected

Digital Image Access & Retrieval

The 33th Annual Clinic on Library Applications of Data Processing, held at the University of Illinois at Urbana-Champaign in March of 1996, addressed the theme of "Digital Image Access & Retrieval." The papers from this conference cover a wide range of topics concerning digital imaging technology for visual resource collections. Papers covered three general areas: (1) systems, planning, and implementation; (2) automatic and semi-automatic indexing; and (3) preservation with the bulk of the conference focusing on indexing and retrieval.published or submitted for publicatio

System Integration of a Tour Guide Robot

In today\u27s world, people visit many attractive places. On such an occasion, It is of utmost importance to be accompanied by a tour guide, who is known to explain about the cultural and historical importance of places. Due to the advancements in technology, smartphones today have the capability to help a person navigate to any place in the world and can itself act as a tour guide by explaining a significance of a place. However, the person while looking into his phone might not watch his/her step and might collide with other moving person or objects. With a phone tour guide, the person is alone and is missing a sense of contact with other travelers. therefore a human guide is necessary to provide tours for a group of visitors. However, Human tour guides might face tiredness, distraction, and the effects of repetitive tasks while providing tour service to visitors. Robots eliminate these problems and can provide tour consistently until it drains its battery. This experiment introduces a tour-guide robot that can be used on such an occasion. Tour guide robots can navigate autonomously in a known map of a given place and at the same time interact with people. The environment is equipped with artificial landmarks. Each landmark provides information about that specific region. An Animated avatar is simulated on the screen. IBM Watson provides voice recognition and text-to-speech services for human-robot interaction

Focal Spot, Summer 1987

https://digitalcommons.wustl.edu/focal_spot_archives/1046/thumbnail.jp