Download Advances in Visual Computing: 11th International Symposium, by George Bebis, Richard Boyle, Bahram Parvin, Darko Koracin, PDF

By George Bebis, Richard Boyle, Bahram Parvin, Darko Koracin, Ioannis Pavlidis, Rogerio Feris, Tim McGraw, Mark Elendt, Regis Kopper, Eric Ragan, Zhao Ye, Gunther Weber

The quantity set LNCS 9474 and LNCS 9475 constitutes the refereed complaints of the eleventh foreign Symposium on visible Computing, ISVC 2015, held in Las Vegas, NV, united states in December 2015.

The a hundred and fifteen revised complete papers and 35 poster papers awarded during this publication have been rigorously reviewed and chosen from 260 submissions. The papers are prepared in topical sections: half I (LNCS 9474) includes computational bioimaging; special effects; movement and monitoring; segmentation; acceptance; visualization; mapping; modeling and floor reconstruction; advancing autonomy for aerial robotics; clinical imaging; digital fact; looking at people; spectral imaging and processing; clever transportation structures; visible notion and robot platforms. half II (LNCS 9475): purposes; 3D desktop imaginative and prescient; special effects; segmentation; biometrics; development attractiveness; attractiveness; and digital reality.

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Additional info for Advances in Visual Computing: 11th International Symposium, ISVC 2015, Las Vegas, NV, USA, December 14-16, 2015, Proceedings, Part II

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Mach. Intell. 23, 257–267 (2001) Automated Habit Detection System: A Feasibility Study 23 4. : Recognizing human actions: a local SVM approach. In: Proceedings of the 17th International Conference on Pattern Recognition (ICPR), vol. 3, pp. 32–36 (2004) 5. : View invariant human action recognition using histograms of 3D joints. In: 2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pp. 20–27 (2012) 6. : Skeletal quads: human action recognition using joint quadruples.

6 SD from the AMM). Table 2. Confusion matrix in detection of habits. Gold standard Proposed system habit non-habit habit 63 12 non-habit 14 to detect human habits. However, we recognize that several issues need to be addressed to make our system practical. In this experiment, we detected only uncommon motions as habits, focused only on the speed of the motion, and employed a subjective gold standard. We will investigate these issues and develop an improved system in the near future. 5 Conclusion In this study, we proposed a prototype automated habit detection system to objectively recognize unconscious habits.

Christos Papachristos, Dimos Tzoumanikas, Kostas Alexis, and Anthony Tzes Inspection Operations Using an Aerial Robot Powered-over-Tether by a Ground Vehicle . . . . . . . . . . . . . . . . . . . . Lida Zikou, Christos Papachristos, Kostas Alexis, and Anthony Tzes 419 432 444 455 Autonomous Guidance for a UAS Along a Staircase . . . . . . . . . Olivier De Meyst, Thijs Goethals, Haris Balta, Geert De Cubber, and Rob Haelterman 466 Nonlinear Controller of Quadcopters for Agricultural Monitoring .

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