Machine vision: cost-effective action

[Audio Version]

Following is another in my series of ad hoc journal entries I've been keeping of my thoughts on machine vision.

One thing that seems to dog many MV techniques is how slow or otherwise resource-hungry they are. I'm realizing that one thing that seems a must is a set of basic vision tools that allow for trading time for effectiveness. For example, given a whole image, the agent should be able to focus on a small portion - like your own fovea does - instead of trying to analyze the entire image. Also, the agent should be able to choose a lower quality image in order to reducing processing time.

Ideally, an agent would be able to learn to estimate how much time each operation will take and to thus be able to choose which techniques to use and how intently to apply them based on how well they serve various goals. If, for example, the goal is to track the movement of one or more objects, a full-image, low-res approach might do. To study a stationary object in detail, by contrast, might suggest a small-portion, high-res approach.

Comments

Popular posts from this blog

Coherence and ambiguities in problem solving

Neural network in C# with multicore parallelization / MNIST digits demo

Back in the saddle / C# neural network demo