Advantages of cv::Matx

Question

I noticed that a new data structure cv::Matx was added to the new OpenCV version, intended for small matrices of known size at compilation time, for example

cv::Matx31f  // matrix 3x1 of float type 

Checking the documentation I saw that most of matrix operations are available, but still I don't see the advantages of using this new type instead of the old cv::Mat.

When should I use Matx instead of Mat?

Answer 1

It's about memory management and not wasting (in some cases important) memory or just reservation of memory for an object you'll use later.

That's how I understand it – may be someone else can give a better explanation.

Answer 2

Short answer: cv::Mat uses the heap to store its data, while cv::Matx uses the stack.

A cv::Mat uses dynamic memory allocation (on the heap). This is appropriate for big matrices (like images) and lets you do things like shallow copies of a matrix, which is the default behavior of cv::Mat.

However, for the small matrices that cv::Matx is designed for, heap allocation would be very expensive compared to doing the same thing on the stack. I have seen a block of math reduce processing time by over 75% by switching to using stack-allocated types (e.g. cv::Point and cv::Matx) instead of cv::Mat.