A usability survey of a contents-based video retrieval system by combining digital video and an electronic bulletin board

2005 ◽  
Vol 8 (3) ◽  
pp. 251-262 ◽  
Author(s):  
Hirohide Haga ◽  
Shigeo Kaneda
2014 ◽  
Vol 9 (7) ◽  
pp. 1717-1726 ◽  
Author(s):  
Serkan Genç ◽  
Muhammet Baştan ◽  
Uğur Güdükbay ◽  
Volkan Atalay ◽  
Özgür Ulusoy

1986 ◽  
Vol 21 (1) ◽  
pp. 40-47
Author(s):  
Richard M. Neustadt

Since this is a legal seminar, I thought it would be appropriate to begin with a case. There is a person in Los Angeles who has been operating an electronic bulletin board on his personal computer. What that means is that he has memory attached to his computer, and it is possible for anyone else in the country with a computer to dial into that bulletin board and leave a message automatically in the memory. That message can then be accessed by anyone else who dials in.This person does not exercise any control over the messages that are put in. It is open to anyone who wants to put a message in there. Somebody put into that bulletin board the telephone credit card number of a rich person. Subsequently, many other people dialed into the bulletin board, got the telephone credit card number and charged phone calls to that person. No one knows where the number came from. The board operator was prosecuted under a criminal charge. The question is, is he liable?


2021 ◽  
Author(s):  
ElMehdi SAOUDI ◽  
Said Jai Andaloussi

Abstract With the rapid growth of the volume of video data and the development of multimedia technologies, it has become necessary to have the ability to accurately and quickly browse and search through information stored in large multimedia databases. For this purpose, content-based video retrieval ( CBVR ) has become an active area of research over the last decade. In this paper, We propose a content-based video retrieval system providing similar videos from a large multimedia data-set based on a query video. The approach uses vector motion-based signatures to describe the visual content and uses machine learning techniques to extract key-frames for rapid browsing and efficient video indexing. We have implemented the proposed approach on both, single machine and real-time distributed cluster to evaluate the real-time performance aspect, especially when the number and size of videos are large. Experiments are performed using various benchmark action and activity recognition data-sets and the results reveal the effectiveness of the proposed method in both accuracy and processing time compared to state-of-the-art methods.


Author(s):  
Gavin Mueller

This paper examines the organization of digital piracy in the context of reshaping labor under neoliberalism. It discusses the practices by which enclosures of intellectual property are resisted by drawing from literature on the labor process, and examining the historical emergence of piratical practice on electronic bulletin board systems. These pirates sought, above all, to preserve autonomous, self-managed working conditions in the face of tendencies to commodify, enclose, and deskill.


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