scholarly journals Coview: A Cooperative Architecture for Digital Video Editing

2006 ◽  
Vol 115 (11-12) ◽  
pp. 482-491 ◽  
Author(s):  
Benjamim Fonseca ◽  
Eurico Carrapatoso
Keyword(s):  
2012 ◽  
Vol 3 (4) ◽  
pp. 123-134 ◽  
Author(s):  
Kevin Romig

Most classroom instruction related to urban geography and design relies heavily on static photographic images that highlight form, but don’t necessarily engage the idea of function. Because of the relative ease of digital video editing and the portability of high-definition digital video cameras, using instructor-collected video in the classroom is less-demanding than in the past. This paper highlights how short video vignettes can better elucidate urban concepts and explains best practices in crafting educational objectives and professional video products.


2012 ◽  
pp. 845-858
Author(s):  
Sarah Atkinson

This chapter focuses upon a case study of an online higher education intervention – an interactive resource the author has devised as an aid to the teaching and learning of undergraduate digital video editing (DVE). This resource specifically addresses drama and fiction postproduction principles, practice and techniques. The repository, which includes streamed materials available to download, guides the student through the film production process in a step-by-step way (for students), with suggested class based activities and tasks using the materials (for tutors). The resources include the script, all planning documentation, all production paperwork, and all rushes shot for different productions. The student/tutor navigates through these materials guided by a combination of voice-overs, video tutorials by those personnel involved in the production, and clips taken from the “making of” documentaries. This chapter explores the intervention within the wider context of higher education online teaching and through the lens of virtual learning environment pedagogic theory.


Author(s):  
Ramesh Chand Pandey ◽  
Sanjay Kumar Singh ◽  
K. K. Shukla

With increasing availability of low-cost video editing softwares and tools, the authenticity of digital video can no longer be trusted. Active video tampering detection technique utilize digital signature or digital watermark for the video tampering detection, but when the videos do not include such signature then it is very challenging to detect tampering in such video. To detect tampering in such video, passive video tampering detection techniques are required. In this chapter we have explained passive video tampering detection by using noise features. When video is captured with camera it passes through a Camera processing pipeline and this introduces noise in the video. Noise changes abruptly from authentic to forged frame blocks and provides a clue for video tampering detection. For extracting the noise we have considered different techniques like denoising algorithms, wavelet based denoising filter, and neighbor prediction.


SMPTE Journal ◽  
1990 ◽  
Vol 99 (8) ◽  
pp. 634-638
Author(s):  
Larry J. Gardner ◽  
David H. Scoggins

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