Advances in Visual Computing: 12th International Symposium, by George Bebis, Richard Boyle, Bahram Parvin, Darko Koracin,

By George Bebis, Richard Boyle, Bahram Parvin, Darko Koracin, Fatih Porikli, Sandra Skaff, Alireza Entezari, Jianyuan Min, Daisuke Iwai, Amela Sadagic, Carlos Scheidegger, Tobias Isenberg

The quantity set LNCS 10072 and LNCS 10073 constitutes the refereed lawsuits of the twelfth overseas Symposium on visible Computing, ISVC 2016, held in Las Vegas, NV, united states in December 2016.

The 102 revised complete papers and 34 poster papers awarded during this ebook have been conscientiously reviewed and chosen from 220 submissions. The papers are equipped in topical sections: half I (LNCS 10072) includes computational bioimaging; special effects; movement and monitoring; segmentation; trend acceptance; visualization; 3D mapping; modeling and floor reconstruction; advancing autonomy for aerial robotics; clinical imaging; digital fact; computing device imaginative and prescient as a provider; visible belief and robot platforms; and biometrics. half II (LNCS 9475): functions; visible surveillance; special effects; and digital reality.

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Extra info for Advances in Visual Computing: 12th International Symposium, ISVC 2016, Las Vegas, NV, USA, December 12-14, 2016, Proceedings, Part I (Lecture Notes in Computer Science)

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Xin Zhou, Guangming Shi, and Wei Zhou 75 Video Anomaly Detection Based on Adaptive Multiple Auto-Encoders . . . Tianlong Bao, Chunhui Ding, Saleem Karmoshi, and Ming Zhu Comprehensive Parameter Sweep for Learning-Based Detector on Traffic Lights . . . . . . . . . . . . . . . . . . . . . . . . . Morten B. Jensen, Mark P. Philipsen, Thomas B. Moeslund, and Mohan Trivedi 83 92 XXXII Contents – Part II An Efficient Pedestrian Detector Based on Saliency and HOG Features Modeling .

Localization of OD region: (a). Segmented candidate OD regions (b). OD region after using vessel information Fig. 9. Determination of ROI: (a). ROI marked in blue box and center of detected OD’s region marked in black, (b). ROI region. 4 Boundary Detection of OD by Variation Along Line Profile In our dataset, the OD region has the most discriminating appearance in the red color plane, as mentioned before. However, in some sub-images, the fundus regions other than OD appears brighter due to intra-image variations and makes the appearance of OD as non-discriminating in red channel.

Huaixin Xiong 464 Reduction of Missing Wedge Artifact in Oblique-View Computed Tomography . . . . . . . . . . . . . . . . . . . . . . . Kyung-Chan Jin, Jung-Seok Yoon, and Yoon-Ho Song 475 Contents – Part II Using Dense 3D Reconstruction for Visual Odometry Based on Structure from Motion Techniques . . . . . . . . . . . . . . . . . . . Marcelo de Mattos Nascimento, Manuel Eduardo Loaiza Fernandez, and Alberto Barbosa Raposo XXXV 483 Towards Estimating Heart Rates from Video Under Low Light.

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