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There are video distribution solutions that destroys a video file after watching, but are there formats which can be customized to deteriorate in video quality (but not audio quality) with time? This would encourage students to watch lectures when they show up on an LMS, and not procrastinate. It could also be nice for the teacher to know that his or hers makeshift lectures, not intended to become any classics, were watchable only for a period of time. Next year the lectures will be different - but if necessary the teacher has the original video file from last year to customize in time -it begins to deteriorate after say three days, and there is only audio after a week. Are there such fomats? Used them? Is it a good idea?
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You have to examine what the purpose of the video is in the overall scheme of things. If this is important information to the overall development of a particular competency in the class, then you are defeating your purpose to either remove it or have it go bad after a few days. Students learn in different ways. Sometime a student needs to review that video more than once to fully grasp the concept. 
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I am planning an experiment in which participants will provide perceptual evaluations of images of streets at night. I would like to ensure as best as possible that the photos simulate the range of luminances and spectra that would be experienced by someone viewing the same streets at night in the real world. I am particularly interested in ensuring the photos reflect differences in the street lighting used on the different streets. For example, if one street has an average luminance under the street lighting that is twice that of another street, how can I ensure the photos of these streets also reflect a similar difference in luminance magnitude?
I am hoping there are image post-processing methods that may be useful in achieving what I want.
Thanks!
Jim Uttley
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I have not dealt with this issue directly, but the following technical papers may be useful (I attended conferences where the recent ones were presented).
There is also a useful and interesting, albeit brief, discussion of issues related to the photography of street lighting installations by D. Schreuder in the book "Public Lighting" edited by J. De Boer, 1967, Philips Technical Library, in Chapter 8, "Measurements."
Please note that most of these papers deal with the luminance distribution rather than the spectral distribution. I would be very cautious about being able to reproduce in a meaningful way the spectral distributions of colored light sources in the nighttime environment.
The comments above regarding maintaining constant camera/lens settings are almost certainly crucial to any success.
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The data is taken by cameras carried by dogs involved in rescue operations, so the images present:
- Lots of motion due to the camera being attached to the dog's vest (and the dog running, jumping).
- All possible image artifacts: Blur, illumination changes, dust, water in the lense...
I understand it is going to be difficult to obtain "smooth" video, but any improvement in the images will be most welcome.
Thanks !
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here's some simple opencv c++ code for video stabilization based on trajectory smoothing (plus kalman tracking)
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I will be happy to get suggestions for software that could grab still images from video footage without quality loss. I'm in general interested in a software that handling different video formats, although I'm also interested in software that goes well with GoPro Hero 3 black edition, video format .mov in 4K.
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you can use OpenCV
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I'm writing a paper related to abnormal event detection in video. I read some papers but I'm afraid I don't cover enough methods. 
Some papers classify abnormal event detection according to applications. For example, global /  local anomaly detection; crowded / uncrowded scenes. 
At current, all methods I know consists of the following steps:
 Feature computation;
 Transform the aggregated features to certain domains;
 Build a model and perform detection.
Are there any other type of methods?
Any suggestions are welcome!
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There are several methods: First you can extract feature vector for each moving object. Then you can use some probabilistic methods or you cab use some classification methods frame based. Some of this methods are rule based.
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i want to reduces shockes in sequence of video images, did any one have a example code for doing this?
i use OpenCV in C# and i estimate moving velocity of each images related to last image. in fact i use optical flow to extract movement between images.
however, how can i stabilize this images for decline shocked and unwanted fast move in realtime by changing the orientation and shift on the images?
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Dear Prof. Karimi,
                    Thanks for your question. I have attached two references for your kind concern. I think these files will help you for your concern.
Regards,
A.Kar
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We're developing a hazard perception test for young cyclists. We collected a lot of videoclips with hazardous events. The next step would be to create a time frame in which participants can respond to the hazard by clicking on a button. At the end of the clip a score (based on the timeframe in which te hazard develops over time) should be given to the participant. Which software can I use?
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Hi,
Thanks for the fast responses! Psychtoolbox 3 looks very promising. Tomorrow we'll take a look at the other possibilities.