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Object tracking is a critical task which could be used in many applications. The minimum error based l1-tracker is one of the classical tracking algorithms. However, the l1-tracker tracks the target frame-by-frame without considering the continuity of the video. In this paper, a novel improved l1-tracker, Self Adaptive Skipping Levels (SASL), has been proposed. The proposed method takes into consideration...
Brain machine interfaces (BMIs) transform modulation of electroencephalogram (EEG) elicited by cognitive and mental events users voluntarily perform into words and commands in accordance with their intents to communicate with somebody else or machines the users want to control. One of the leading paradigms in BMIs includes a method which utilizes the modulation of a steady state visual evoked potentials...
Ambient Assisted Living (AAL) aims to improve the quality of daily life for all humans in different periods of life. Neural-Computer Interface (NCI) can be used within AAL environments to provide alternative communication means for impaired persons bypassing the need for speech and other motor activities. By monitoring, analyzing and responding to muscular activity (EMG signals) of users, NCI systems...
In this paper, we propose an accurate and real-time positioning method for intelligent road vehicles in urban environments. The proposed method uses a robust lane marking detection algorithm, as well as an efficient shape registration algorithm between the detected lane markings and a GPS based road shape prior, to improve the robustness and accuracy of global localization of a road vehicle. We exploit...
Our goal is to develop robots that naturally engage people in social exchanges. In this paper, we focus on the problem of recognizing that a person is responsive to a robot's request for interaction. Inspired by human cognition, our approach is to treat this as a contingency detection problem. We present a simple discriminative Support Vector Machine (SVM) classifier to compare against previous generative...
Over the past decade, the research of decoding visual stimuli from brain signal recorded during a person viewing the image is developing fast as a challenging and up to date work in the neural decoding field. Previous studies have demonstrated that it's possible to identify the one of a set of natural images from human brain activity. In neural decoding studies, the computational model played a key...
Adaptive learning systems require student model repository that store student's data in order to provide learning materials tailored to the student's characteristics. Student's learning style is one of the most crucial factors to be identified in order to update the student's profile. Hence, the need for a high accurate classifier that deals with the students data and generates suitable number of...
We are presenting a novel hybrid mobile localization system for smart mobile devices which combines the prevalence of classical wireless methods with accuracy of computer vision techniques. In the proposed framework, initial localization is roughly measured through classical wireless methods. Later computer vision techniques are deployed to refine the measurement. Specifically an image acquired by...
Features used for classification play essential role in the performance of system. In the field of Lip reading, features appear in large number which has to be solved by selection of subset of features. Work covered in this paper validates the performance of individual visual features such as lip height, lip width, area of lip region, angles at corners and then combine them to create a new subset...
The problem of gender recognition using visual and acoustic cues has recently received significant attention. This paper explores the use of Total Variability (i-vectors) and Inter-Session Variability (ISV) modeling techniques for both unimodal and bimodal gender recognition, and compares them to several state-of-the-art algorithms. The experimental evaluation is conducted on the FERET and LFW databases...
Visualizing information extracted from text is helpful for intuitively understanding the information. Extracting and visualizing personal relationships from text is one of the promising applications of this approach. Existing methods usually estimate personal relationships from direct co-occurrences of personal names that appear in a text. In our previous work, we proposed a method for extracting...
In this paper, we present a real time 3D SLAM system for texture-less scenes using only the depth information provided by a low cost RGB-D sensor. The proposed registration method is based on a novel informative sampling scheme that is able to extract the points carrying the most useful information from two consecutive frames. Those points are assigned 3D feature descriptors and matched with their...
It is very important to identify the measuring position for measuring spatial electromagnetic field distributions. Our Previous studies have proposed various tracking methods for obtaining measurement position automatically by using a magnetic tracker, an optical tracker and an infrared tracker. In this study, we newly introduce measuring method which uses a Kinect as a position sensor. A measuring...
Wireless visual sensor networks (WVSN) have been developed as a directional types of sensor network with different challenges such as optimization of energy consumption. These networks provide more information than the other types of wireless sensor networks. The goal of this paper is to optimize the tradeoff between the energy consumption and the quality of the received data. For realization of this...
A novel low-complexity visual saliency detection algorithm for detecting salient regions in images is proposed. The algorithm derives salient regions based on in-focus regions and image centre sensitivity. The performance of the algorithm in predicting human eye fixations is validated against ten state-of-the-art algorithms using a public image dataset. The results demonstrate that the proposed algorithm...
In this work, we address the problem of building recognition as a mobile application. Our approach exploits a small-sized vocabulary-tree of SIFT descriptors. Each SIFT descriptor in our dataset is saved along with its class label, its nearest neighbor from the vocabulary and the visual words corresponding to its spatial neighbors. To evaluate a new query image, we extract SIFT interest points and...
This paper presents work towards the development of an accurate binocular eye tracking system for 3DTV-Applications. For that to happen, virtual modeling of eye tracking data is prepared. The model is based on defined suitable parameters considering a wide range of complex influencing factors from the distinctive binocular use case. This work in progress presentation is concluded by results of an...
In modern society about 10% of children experience difficulty in learning to read. They suffer from a neuro-developmental disorder called dyslexia. Scientific research has shown that the ability to play action video games improves reading skills of dyslexic children. MADRIGALE research aims at designing and implementing an educational action game oriented to promote, through forms of engaging and...
Steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs) have potential to realize high-speed communication between the human brain and the external environment. Recently, multiple access (MA) methods in telecommunications have been introduced into the system design of BCIs and showed their potential in improving BCI performance. This study investigated the feasibility of...
Rapid serial visual presentation (RSVP) tasks, in which participants are presented with a continuous sequence of images in one location, have been used in combination with electroencephalography (EEG) in a variety of Brain-Machine Interface (BMI) applications. The RSVP task is advantageous because it can be performed at a high temporal rate. The rate of the RSVP sequence is controlled by the stimulus...
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