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                <text>Conference Papers</text>
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    <name>Conference Paper</name>
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              <text>Estimation of Vehicle Distance Based on Feature Points Using Monocular Vision</text>
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              <text>Distance estimation; Monocular vision; Stereo vision</text>
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              <text>In this digital era safety and security have the highest precedence, the advanced driver assistance system is the latest trend and where many challenges are open for researchers. Vehicle to vehicle distance estimation is one of the most important challenges to provide the security and safety alerts for the driver. In order to achieve this, image of the front vehicle is captured using the single camera under monocular vision to estimate the vehicle distance. Then three key steps are designed to estimate the vehicle distance: extracting and locating the key features of the vehicle, characteristic triangle is drawn between those features to calculate pixel area and develop the measuring formula to calculate the distance. For efficient feature extraction and localizing of the feature position, conventional AdaBoost algorithm is utilized to find the strong features for scalable samples. Distance measurement formulation is used to derive the correlation between the pixel area and distance by considering the different parameters from the prototype of pinhole camera, camera standardization and plotting of area. Formula is developed to estimate the optimum moving distance between vehicles to vehicle. After the experimental analysis, the accuracy rate is improved and time complexity satisfies the precision.  2019 IEEE.</text>
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              <text>Arunkumar K.L.; Danti A.; Manjunatha H.T.</text>
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              <text>2019 International Conference on Data Science and Communication, IconDSC 2019</text>
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              <text>Institute of Electrical and Electronics Engineers Inc.</text>
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              <text>2019-01-01</text>
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              <text>&lt;a href="https://doi.org/10.1109/IconDSC.2019.8816996" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1109/IconDSC.2019.8816996&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85072773098&amp;amp;doi=10.1109%2FIconDSC.2019.8816996&amp;amp;partnerID=40&amp;amp;md5=227744393de0167637af1464e2d6e2f3" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85072773098&amp;amp;doi=10.1109%2fIconDSC.2019.8816996&amp;amp;partnerID=40&amp;amp;md5=227744393de0167637af1464e2d6e2f3&lt;/a&gt;</text>
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              <text>Restricted Access</text>
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              <text>ISBN: 978-153869319-3</text>
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              <text>Online</text>
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              <text>English</text>
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              <text>Arunkumar K.L., Department of Computer Applications, Jawaharlal Nehru National College of Engineering, Shimoga, Karnataka, India; Danti A., Department of Computer Science and Engineering, Christ, Deemed to be University, Bangalore, India; Manjunatha H.T., Department of Computer Applications, Jawaharlal Nehru National College of Engineering, Shimoga, Karnataka, India</text>
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