Abstract
Emerging interfaces for video collections of places attempt to link similar content with seamless transitions. However, the automatic computer vision techniques that enable these transitions have many failure cases which lead to artifacts in the final rendered transition. Under these conditions, which transitions are preferred by participants and which artifacts are most objectionable? We perform an experiment with participants comparing seven transition types, from movie cuts and dissolves to image-based warps and virtual camera transitions, across five scenes in a city. This document describes how we condition this experiment on slight and considerable view change cases, and how we analyze the feedback from participants to find their preference for transition types and artifacts. We discover that transition preference varies with view change, that automatic rendered transitions are significantly preferred even with some artifacts, and that dissolve transitions are comparable to less-sophisticated rendered transitions. This leads to insights into what visual features are important to maintain in a rendered transition, and to an artifact ordering within our transitions.
Supplemental Material
Available for Download
Supplemental movie and image files for, Preference and artifact analysis for video transitions of places
- Ballan, L., Brostow, G. J., Puwein, J., and Pollefeys, M. 2010. Unstructured video-based rendering: interactive exploration of casually captured videos.ACM Trans. Graph. 29, 4, 1. Google ScholarDigital Library
- Borg, I. and Groenen, P. 2010. Modern Multidimensional Scaling: Theory and Applications. Springer Series in Statistics.Google Scholar
- Chaurasia, G., Sorkine, O., Drettakis, G., and Inria, R. 2011. Silhouette-aware warping for image-based rendering. In Proceedings of the Eurographics Symposium on Rendering. Google ScholarDigital Library
- Cui, C. 2000. Comparison of two psychophysical methods for image color quality measurement: paired comparison and rank order. In Proceedings of the 8th Color Imaging Conference on Color Science and Engineering Systems, Technologies and Applications (CIC'00). IS&T, 222--227.Google Scholar
- Debevec, P., Yu, Y., and Borshukov, G. 1998. Efficient View-dependent image-based rendering with projective texturemapping. In Rendering Techniques 98: Proceedings of the Eurographics Workshop, Number CSD-98-1003.Google Scholar
- Debuchi, J. 1982. Frozen Time {film}.Google Scholar
- Dmytryk, E. 1984. On Film Editing.Google Scholar
- Eisemann, M., Decker, B. D., Magnor, M., Bekaert, P., de Aguiar, E., Ahmed, N., Theobalt, C., and Sellent, A. 2008. Floating textures. Comput. Graphics Forum 27, 2, 409--418.Google ScholarCross Ref
- Engeldrum, P. G. 2000. Psychometric Scaling: A Toolkit for Imaging Systems Development. Imcotek Press, Winchester, MA.Google Scholar
- Fincher, D. 2002. Panic Room {film}.Google Scholar
- Fischler, M. A. and Bolles, R. C. 1981. Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography. Comm. ACM 24, 6, 381--395. Google ScholarDigital Library
- Furukawa, Y., Curless, B., Seitz, S. M., and Szeliski, R. 2010. Towards Internet-scale multi-view stereo. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 1434--1441.Google Scholar
- Furukawa, Y. and Ponce, J. 2010. Accurate, dense, and robust multi-view stereopsis. IEEE Trans. Pattern Anal. Mach. Intell. 32, 8, 1362--1376. Google ScholarDigital Library
- Goesele, M., Ackermann, J., Fuhrmann, S., Haubold, C., and Klowsky, R. 2010. Ambient point clouds for view interpolation. ACM Trans. Graph. 29, 4, 1--6. Google ScholarDigital Library
- Hartley, R. and Zisserman, A. 2004. Multiple View Geometry in Computer Vision 2nd Ed. Cambridge University Press. Google ScholarDigital Library
- Horry, Y., Anjyo, K.-I. A., and Arai, K. 1997. Tour Into The Picture: Using a Spidery Mesh Interface to make Animation from a Single Image. In Proceedings of the ACM SIGGRAPH International Conference on Computer Graphics and Interactive Techniques. 225--232. Google ScholarDigital Library
- Kazhdan, M., Bolitho, M., and Hoppe, H. 2006. Poisson surface reconstruction. In Proceedings of the Eurographics Symposium on Geometry Processing. Eurographics Association, 61--70. Google ScholarDigital Library
- Lipski, C., Linz, C., Neumann, T., Wacker, M., and Magnor, M. 2010. High Resolution Image Correspondences for Video Post-Production. In Proceedings of the European Conference on Visual Media Production. IEEE, 33--39. Google ScholarDigital Library
- Lourakis, M. I. A. and Argyros, A. A. 2004. The design and implementation of a generic sparse bundle adjustment software package based on the Levenberg-Marquardt algorithm. ICSFORTH Tech. rep. TR 340, 340.Google Scholar
- Lowe, D. G. 2004. Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vision 60, 2, 91--110. Macmillan, J. 1984. Early Work {film}. Google ScholarDigital Library
- Mccurdy, N. J. 2007. RealityFlythrough: A system for ubiquitous video. Ph.D. thesis, University of California, San Diego. Google ScholarDigital Library
- Morvan, Y. and O'Sullivan, C. 2009a. A perceptual approach to trimming and tuning unstructured lumigraphs. ACM Trans. Appl. Percept. 5, 4, 19:1--19:24. Google ScholarDigital Library
- Morvan, Y. and O'Sullivan, C. 2009b. Handling occluders in transitions from panoramic images: A perceptual study. ACM Trans. Appl. Percept. 6, 4, 1--15. Google ScholarDigital Library
- Murch, W. 2001. In the Blink of an Eye. Silman-James Press.Google Scholar
- Mustafa, M., Guthe, S., and Magnor, M. 2012. Single-trial EEG Classification of Artifacts in Videos. ACM Trans. Appl. Percept. 9, 3, 12:1--12:15. Google ScholarDigital Library
- Oh, B. M., Chen, M., Dorsey, J., and Durand, F. 2001. Image-based modeling and photo editing. In Proceedings of the ACM SIGGRAPH International Conference on Computer Graphics and Interactive Techniques. ACM Press, New York, 433--442. Google ScholarDigital Library
- Schaefer, S., Mcphail, T., and Warren, J. 2006. Image deformation using moving least squares. ACM Trans. Graph. 25, 3, 533. Google ScholarDigital Library
- Snavely, N., Garg, R., Seitz, S. M., and Szeliski, R. 2008. Finding paths through the world's photos. ACM Trans. Graph. 27, 3, 1. Google ScholarDigital Library
- Snavely, N., Seitz, S. M., and Szeliski, R. 2006. Photo tourism: Exploring photo collections in 3D. ACM Trans. Graph. 25, 835--846. Google ScholarDigital Library
- Stich, T., Linz, C., Wallraven, C., Cunningham, D., and Magnor, M. 2011. Perception-motivated interpolation of image sequences. ACM Trans. Appl. Percept. 8, 2, 11:1--11:25. Google ScholarDigital Library
- Thormählen, T. 2006. Zuverlässige Schä tzung der Kamerabewegung aus einer Bildfolge. Ph.D. thesis, Universität Hannover.Google Scholar
- Tompkin, J., Kim, K. I., Kautz, J., and Theobalt, C. 2012. Videoscapes: Exploring Sparse, Unstructured Video Collections. ACM Trans. Graph. 31, 4. Google ScholarDigital Library
- Torgerson, W. S. 1958. Theory and Methods of Scaling. Wiley, New York.Google Scholar
- Vangorp, P., Chaurasia, G., Laffont, P.-Y., Fleming, R. W., and Drettakis, G. 2011. Perception of visual artifacts in image-based rendering of façades. In Proceedings of the Eurographics Symposium on Rendering. Google ScholarDigital Library
- Vangorp, P., Richardt, C., Cooper, E. A., Chaurasia, G., Banks, M. S., and Drettakis, G. 2013. Perception of perspective distortions in image-based rendering. ACM Trans. Graph. 32, 4. Google ScholarDigital Library
Index Terms
- Preference and artifact analysis for video transitions of places
Recommendations
Summarization of Neonatal Video EEG for Seizure and Artifact Detection
NCVPRIPG '11: Proceedings of the 2011 Third National Conference on Computer Vision, Pattern Recognition, Image Processing and GraphicsMonitoring neonatal EEG signal is useful in identifying neonatal convulsions or seizures. For neonates, seizures can be electrographic, electro clinical, or both simultaneously. Electrographic seizure is identified via recorded EEG signal, while electro ...
Artifact Processing of Epileptic EEG Signals: An Overview of Different Types of Artifacts
ACSAT '13: Proceedings of the 2013 International Conference on Advanced Computer Science Applications and TechnologiesThe electroencephalogram (EEG) signal contains a plethora of information regarding a human brain and thus plays a very important role when it comes to the diagnosis of various neurological disorders. The quantitative analysis of epileptic EEG can ...
Spatiotemporal transitions in temporal lobe epilepsy
Quantitative neuroscienceEpilepsy is a common neurological disorder characterized by recurrent seizures, most of which appear to occur spontaneously as a result of complex dynamical interactions among many regions of the brain. The most common type of epilepsy in adults is ...
Comments