Graph cuts and active contours are two very popular interactive object segmentation techniques in the field of computervision and imageprocessing. However, both these approaches have their own well-known limitations...
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ISBN:
(数字)9781510619951
ISBN:
(纸本)9781510619951
Graph cuts and active contours are two very popular interactive object segmentation techniques in the field of computervision and imageprocessing. However, both these approaches have their own well-known limitations. Graph cut methods perform efficiently giving global optimal segmentation result for smaller images. However, for larger images, huge graphs need to be constructed which not only takes an unacceptable amount of memory but also increases the time required for segmentation to a great extent. On the other hand, in case of active contours, initial contour selection plays an important role in the accuracy of the segmentation. So a proper selection of initial contour may improve the complexity as well as the accuracy of the result. In this paper, we have tried to combine these two approaches to overcome their above-mentioned drawbacks and develop a fast technique of object segmentation. Here, we have used a pyramidal framework and applied the mincut/maxflow algorithm on the lowest resolution image with the least number of seed points possible which will be very fast due to the smaller size of the image. Then, the obtained segmentation contour is super-sampled and and worked as the initial contour for the next higher resolution image. As the initial contour is very close to the actual contour, so fewer number of iterations will be required for the convergence of the contour. The process is repeated for all the high-resolution images and experimental results show that our approach is faster as well as memory efficient as compare to both graph cut or active contour segmentation alone.
indian Classical Dance (ICD) is a living heritage of India. Traditionally Gurus (teachers) are the custodians of this heritage. They practice and pass on the legacy through their Shishyas (disciples), often in undocum...
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Drought stress detection involves multi-modal image analysis with high spatio-temporal resolution. Identification of digital traits that characterizes drought stress response (DSR) is challenging due to high volume of...
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We present an approach for Human Action Recognition based on amalgamation of features from depth maps and body-joint data. This Integrated feature set consists of depth features based on gradient orientation and motio...
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Although Deep Convolutional Neural Networks trained with strong pixel-level annotations have significantly pushed the performance in semantic segmentation, annotation efforts required for the creation of training data...
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The problem of automatically extracting anomalous events from any given video is a problem that has been researched from the early days of computervision. It has still not been fully solved, showing that it is indeed...
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This book presents new theories and working models in the area of data analytics and learning. The papers included in this volume were presented at the first International conference on Data Analytics and Learning (DA...
ISBN:
(纸本)9789811325137
This book presents new theories and working models in the area of data analytics and learning. The papers included in this volume were presented at the first International conference on Data Analytics and Learning (DAL 2018), which was hosted by the Department of Studies in computer Science, University of Mysore, India on 3031 March 2018. The areas covered include pattern recognition, imageprocessing, deep learning, computervision, data analytics, machine learning, artificial intelligence, and intelligent systems. As such, the book offers a valuable resource for researchers and practitioners alike.
Recently, near-infrared to visible light facial image matching is gaining popularity, especially for low-light and night-time surveillance scenarios. Unlike most of the work in literature, we assume that the near-infr...
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In recent days, it is found that Synthetic Aperture Radar (SAR) images can be a very useful mode for observing and understanding the surface of Earth. The images formed under SAR modality usually suffer from multiplic...
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Automatic techniques to recognize and evaluate digital logic circuits are more efficient and require less human intervention, as compared to, traditional pen and paper methods. In this paper, we propose LEONARDO (Logi...
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