OpenCV books about handling real life scenarios
Hello,
I'm new to OpenCV, to get started I've been following the official online tutorials and I've been reading the following books:
- Practical Python and OpenCV
- OpenCV Computer Vision With Python [Packt]
- Practical OpenCV [Apress] (currently reading)
Very interesting books to get started, however I'm noticing even if now I know how to call the various OpenCV functions I have very little clue about how to apply this to real case scenario.
Does anyone have suggestion about books/tutorials/papers about how to gracefully use opencv in real case scenario ?
Specifically I'm interested in techniques about how to segment an indoor/outdoor scene and the movements of those segments.
Any suggestion is welcome :)
--- EDIT: Adding details ---
What I'm currently trying to archive is using the face as "natural" user interface, the idea is to partially move the camera into 3D environment (it's an educational tool developed by a friend) the scene it's quite simple, it has a single object in the middle
Getting close: Zoom In
Moving away: Zoom Out
Looking from top/bottom/left/right: rotate the object top/bottom/left/right
Currently I'm trying in this way: Attempt
- Calibration: using Haar cascade for find the face initially, extracting keypoints and descriptor in the area of the face and storing as "neutral" position
- Run: calculating the homography to obtain the trasformation matrix of the plane of the face
Problems:Problems
- Haar cascade it's very delicate, so if the head tilt or rotate I lose the tracking
- The background it's not "clean" but it's a random scene
Ideas:
- Possible solutions
- Continuously tracking and updating the shape of the face (problem: with the little i know segmenting the image and isolating the shape of the head from the rest of the scene it's
messy)
- messy) - matching the face with hist and backproject (future
attempt)
- attempt) - using absdiff for detecting movements (future attempt)
How would you proceed in such a case ?
