Predator: Tracking + Learning

Zdenek Kalal has come up with a system that can quickly learn how to track objects in a video stream. The demo is quite interesting. The related papers are mentioned at the end of the video (and also on Zdenek's website).

To decide if the tracking algorithm is actually so robust or not, I'll have to go through the papers. But for now, the video is quite impressive. Oh, by the way, this isn't an april fool's video ;)

OpenCV Face Detection Visualized

This video visualizes the detection process of OpenCV's face detector. The algorithm uses the Viola Jones method of calculating the integral image and then performing some calculations on all the areas defined by the black and white rectangles to analyze the differences between the dark and light regions of a face. The sub-window (in red) is scanned across the image at various scales to detect if there is a potential face within the window. If not, it continues scanning. If it passes all stages in the cascade file, it is marked with a red rectangle. But this does not yet confirm a face. In the post-processing stage all the potential faces are checked for overlaps. Typically, 2 or 3 overlapping rectangles are required to confirm a face. Loner rectangles are rejected as false-positives.

New statistical model of vision

The human retina is made up of approximately 100 million light sensitive cells. This is enough to overload all neurons in the brain. So, people believed that the brain somehow reduced this information overload - by interpreting things in terms of horizontal, vertical and diagonal lines. Then, combining these lines and edges into objects that could be recognized.

But recently, Ruth Rosenholtz put forward a model that this happens only near the center of the retina. At the periphery, things a quite different. The brain does not interpret signals from the periphery as good as the center - a phenomenon you can feel physically (there's a test at the bottom link).

Earlier, this was just a side comment. There wasn't any mathematical model to account for this peculiarity. This new model of vision is converting that into numbers and calculations!

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Tic Tac Toe + OpenCV

Here's an interesting video I watched on YouTube today. It has sparked some interesting ideas, similar to the SuDoKu Grabber. Lets see if I can create something!

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