By Lourdes Agapito, Michael M. Bronstein, Carsten Rother
The four-volume set LNCS 8925, 8926, 8927, and 8928 includes the completely refereed post-workshop lawsuits of the Workshops that came about together with the thirteenth eu convention on desktop imaginative and prescient, ECCV 2014, held in Zurich, Switzerland, in September 2014.
The 203 workshop papers have been conscientiously reviewed and chosen for inclusion within the court cases. They the place awarded at workshops with the subsequent issues: the place desktop imaginative and prescient meets paintings; desktop imaginative and prescient in automobile expertise; spontaneous facial habit research; client intensity cameras for machine imaginative and prescient; "chalearn" humans: pose, restoration, action/interaction, gesture attractiveness; video occasion categorization, tagging and retrieval in the direction of monstrous info; machine imaginative and prescient with neighborhood binary development versions; visible item monitoring problem; laptop imaginative and prescient + ontology applies cross-disciplinary applied sciences; visible conception of affordance and useful visible primitives for scene research; graphical versions in laptop imaginative and prescient; gentle fields for laptop imaginative and prescient; computing device imaginative and prescient for highway scene knowing and self reliant riding; gentle biometrics; moving and adapting resource wisdom in machine imaginative and prescient; surveillance and re-identification; colour and photometry in laptop imaginative and prescient; assistive computing device imaginative and prescient and robotics; computing device imaginative and prescient difficulties in plant phenotyping; and non-rigid form research and deformable picture alignment. also, a panel dialogue on video segmentation is included.
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Extra info for Computer Vision - ECCV 2014 Workshops: Zurich, Switzerland, September 6-7 and 12, 2014, Proceedings, Part IV
At the same time, the interface with round shape visualization 1 JavaCV is a wrapper library for OpenCV  library. Combining Semi-autonomous Navigation with Manned Behaviour Fig. 4. Pilot interface with round shape drivable area visualization Fig. 5. Pilot interface with a corridor-like drivable area visualization 23 24 A. Kiselev et al. helps users to identify obstacles in the sides of the robot. Nevertheless, the drivable area discovery and obstacle avoidance algorithms behind both visualization methods are identical and use the same region of interest to cope with obstacles in front and on the sides of the robot.
This limitation does not also allow the robot to traverse the overexposed area in Fig. 7d. One possible way to address the issue with light blobs in the future is to track them in motion according to the robot’s actual speed. Another issue seen in Fig. 7c is the margin between two diﬀerent areas. Although both areas are classiﬁed as drivable according to the local ﬂoor samples captured in both areas, the margin between them is still considered as an obstacle due to the straight line detection stage.
Smart camera based monitoring system and its application to assisted living. Proceedings of the IEEE 96(10), 1698–1714 (2008) 10. : What is usual in unusual videos? trajectory snippet histograms for discovering unusualness. In: CVPR 2014 2nd Workshop on Web-scale Vision and Social Media (VSM) 11. : Knives are picked before slices are cut: recognition through activity sequence analysis. In: Proceedings of the 5th international workshop on Multimedia for cooking & eating activities. pp. 3–8. ACM (2013) 12.
Computer Vision - ECCV 2014 Workshops: Zurich, Switzerland, September 6-7 and 12, 2014, Proceedings, Part IV by Lourdes Agapito, Michael M. Bronstein, Carsten Rother