1 / 10

Video and stills data

Video and stills data. Took a short video with a simple stills camera: 640x480 30fps No camera motion. Some people motion Used open-source video denoising ( Ffmpeg project) to get rid of some camera random noise. Took multiple exposures stills from (almost) the same viewpoint

prema
Download Presentation

Video and stills data

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Video and stills data • Took a short video with a simple stills camera: 640x480 30fps • No camera motion. • Some people motion • Used open-source video denoising (Ffmpeg project) to get rid of some camera random noise. • Took multiple exposures stills from (almost) the same viewpoint • High resolution • 3 exposures • Fused together using “Exposure Fusion”

  2. A single video frame

  3. 3 exposure level stills

  4. Fused image • a better fusion or HDR composition is probably possible…

  5. started with a single video frame. Did SIFT matching of the video frame and fused still image.

  6. Homography fitting • Fitting an homography using RANSAC • Result on next slide – flicker back and forth

  7. flicker back and forth

  8. The problems • Alignment error because: • The real world geometry is not planar. • Error in SIFT-less areas. • Scene motion • How to handle people walking into the scene?

  9. Suggested algorithm overview • For each pixel in the video frame: • If a patch around it is “clipped” (all 255 or all 1, due to extreme over/under exposure), I have no information other than the homography, take the color from the fused image according to the homography. • Otherwise, compare the patch in the video frame with patches that are up to 5 pixels from where the homography indicates. Take the best one, and take that patch’s center’s color for this pixel. If no patch is good enough – keep original color (to help keep the people in the video). • How to compare patches?

  10. Patch comparison • Since the patches where shot at different exposures, I can’t compare color. • But Camera response curve is monotonic – i.e more light equals a brighter pixel. • Transform each patch into a “gradient direction vector”: • For each two neighboring pixels, take + if the intensity increases, - if decreases, 0 it’s the same. • A 3x3 patch is transformed into 20 trinary values. Comparison is done in this space.

More Related