Sarath Kodagoda

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Driver drowsiness and loss of vigilance are a major cause of road accidents. Monitoring physiological signals while driving provides the possibility of detecting and warning of drowsiness and fatigue. The aim of this paper is to maximize the amount of drowsiness-related information extracted from a set of electroencephalogram (EEG), electrooculogram (EOG),(More)
Road-boundary detection is an integral and important function in advanced driver-assistance systems and autonomous vehicle navigation systems. A prominent feature of roads in urban, semi-urban, and similar environments, such as in theme parks, campus sites, industrial estates, science parks, and the like, is curbs on either side defining the road's(More)
Lane detection in urban environments is a challenging task. That is mainly due to the non existence of unique models, poor quality of lane markings due to wear, occlusions due to the presence of traffic and complex road geometry. In this work we present a novel lane detection and tracking algorithm for urban road scenarios based on weak models, which is(More)
Surface Electromyogram (EMG) signals are usually utilized as a control source for multifunction powered prostheses. A challenge that arises with the current demands of such prostheses is the ability to accurately control a large number of individual and combined fingers movements and to do so in a computationally efficient manner. As a response to such a(More)
Ability to recognize human activities will enhance the capabilities of a robot that interacts with humans. However automatic detection of human activities could be challenging due to the individual nature of the activities. In this paper, we present human activity detection model that uses only 3-D skeleton features generated from an RGB-D sensor (Microsoft(More)
Application of neuroscience methods to analyze and understand human behavior related to markets and marketing exchange has recently gained research attention. The basic aim is to guide design and presentation of products to optimize them to be as compatible as possible with consumer preferences. This paper investigates physiological decision processes while(More)
quadrotor microaerial vehicles (MAVs) are simple robotic platforms with regard to their construction. In their basic form, they are no more than two counterrotating propeller pairs attached symmetrically to a rigid crosslike frame, along with the means to control the speed of each individual propeller. This symmetric design has enabled the quadrotor to(More)
Scene classification is a fundamental perception task for environmental understanding in today's robotics. In this paper, we have attempted to exploit the use of popular machine learning technique of deep learning to enhance scene understanding, particularly in robotics applications. As scene images have larger diversity than the iconic object images, it is(More)
Driver distraction is regarded as a significant contributor to motor-vehicle crashes. One of the important factors contributing to driver distraction was reported to be the handling and reaching of in-car electronic equipment and controls that usually requires taking the drivers' hands off the wheel and eyes off the road. To minimize the amount of such(More)