Peanut Butter + Jelly

Moition History Image

How to produce Motion History Image

1) Convert Image to silhouette
2) Update motion history image
3) Calculate motion gradient of individual elements
4) Find motion orientation of entire image

Motion gesture recognition systems is based on the idea that it is simple for humans to recognize motions patterns even though the image might be blurred.

Example video.

Standard motion signatures or movements are built into a library. By matching motion history viewed on a camera it is possible to recognize certain movements that a person has performed.

Example video.

Applications
- Entertainment System
- Expression Recognition

Motion History vs Optical Flow
- Optical flow requires sharp edges to recognize points of interest, thus requires a high resolution camera and is computationally more expensive. Added benefit is it can recogize general structures which motion history can not.
- Motion history recognizes general "patterns" of movement, thus can be implemented with cheap cameras and lower powered CPUs. It can also be implemented in low light areas where structure can not be easily detected.

Special thanks to Gary Bradski and James Davis for their research paper - Motion segmentation and pose recognition with motion history gradient.

Posted by ben chao at 10:29 PM | Permalink

Block Path

Blocks as Letters

Blocks as Musical Notes

Blocks as Words

Posted by ben chao at 10:05 PM | Permalink

This is what i did for hw3 . A simple game that challenges the user to match the news title with its brief. Click on any title or story to select. When you have matching title and story, the item is removed. The data is read off of BBC's rss feed.

What's missing
- Generate random order of titles and stories. Right now I just reverse the order for the stories, which isn't too challenging at all.
- Some means to force myself to play this everyday so I can keep up with current events.

Posted by ben chao at 08:24 PM | Permalink