Conference Papers

Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/28506

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Author: search.filters.author.Kalwad, P.

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    Computer interaction based on voluntary ocular motility for the physically challenged
    (2013) Ram, S.; Kalwad, P.
    Ocular Motility is a promising mode of input for human computer interaction. However, we are yet to engineer an application that is cost-effective, robust, user-friendly and far reaching. In this paper we describe an eye-controlled application which will be beneficial to the physically challenged community. Even people who can move only their eyes can use this with ease. This works on principles of Image processing and translates the eye movements into mouse commands, thereby enabling the physically challenged to interact with a computer. A user friendly graphical user interface has been developed to demonstrate the merits of eye controlled input as a natural mode of human-machine interaction. © 2013 IEEE.
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    Reflection removal in smart devices using a prior assisted independent components analysis
    (SPIE spie@spie.org, 2015) Kalwad, P.; Prakash, D.; Peddigari, V.; Srinivasa, P.
    When photographs are taken through a glass or any other semi-reflecting transparent surface, in museums, shops, aquariums etc., we encounter undesired reflection. Reflection Removal is an ill-posed problem and is caused by superposition of two layers namely the scene in front of camera and the scene behind the camera getting reflected because of the semi-reflective surface. Modern day hand held Smart Devices (smartphones, tablets, phablets, etc) are typically used for capturing scenes as they are equipped with good camera sensors and processing capabilities and we can expect image quality to be similar to a professional camera. In this direction, we propose a novel method to reduce reflection in images, which is an extension of Independent Component Analysis (ICA) approach, by making use of two cameras present - a back camera (capturing actual scene) and a front facing camera. When compared to the original ICA implementation, our method gives on an average of 10% improvement on the peak signal to noise ratio of the image. © 2015 SPIE-IS&T.