Work place: Savitribai Phule Pune University, Pune
E-mail: adshaligram@gmail.com
Website:
Research Interests: Image Processing, Image Manipulation, Image Compression, Computer Architecture and Organization, Computer systems and computational processes
Biography
A.D.Shaligam male, is Professor and Head of the Department of Electronic Science, Savitribai Phule Pune University (Formerly University of Pune), Pune, India. He received his M.Sc in 1981 and Ph.D. in 1986 from the Pune University. He has more than 145 publications in the national and international journals. His research interest includes fiber optics and optical wave-guide sensors, PC/ microcontroller based instrumentation, biomedical instrumentation, sensors, wireless sensor networks and image processing.
By Anand G Buddhikot Nitin. M. Kulkarni Arvind.D. Shaligram
DOI: https://doi.org/10.5815/ijigsp.2018.02.02, Pub. Date: 8 Feb. 2018
The infotainment systems are acquiring wide popularity in automotive domain. These systems are manually operated and require physical contact for interaction. In the present scenario the consumers are demanding a smart phone like experience from the vehicle’s console unit. Thus, there is a wide scope for enhancing the mode of interaction and introducing a touch less interface system. The gesture interface approach is a new possibility in this domain. In this method the skin detection plays an important role in segmenting hand region. There are various approaches for hand detection based on skin region identification. The fundamental challenge in skin detection lies in various factors such as illumination, background, camera characteristics, and ethnicity. The gesture detection in automotive environment is further challenging task due to significant impact of wide variation in light, continuous changing background and hindrance caused by vehicle movement. In the present work, design of hand gesture interface for rear seat passenger is discussed. The interface is developed to interact with media player application of infotainment system based on efficient skin detection technique. The objectives of work include study of various skin color modeling, analysis of combination of color spaces, study of hand feature extraction and recognition techniques, design of lab setup for experimentation, implementing gesture interface to access media player application of an infotainment system. The developed prototype lab set up is used for analyzing the skin classifiers and designing a Hi-Vi skin classifier. Further, a user friendly interface is developed using Hi-Vi algorithm with multimode interface features. The evaluation of developed system shows high TPR and low FPR.
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