A couple of years ago, while riding my bike home from work and in a moment of inattentiveness, I collided with the back of a parked, low slung trailer. It was not a particularly pleasant experience and inspired me to create an obstacle alert monitor that could be mounted on my handle bars and sound an alert when an object is approaching (from the vantage point of the camera). My research for a suitable platform led me to the openmv H7.
Here are the things that I think need to happen for each frame:
- Identify any objects in the field of view and mark their location, size, and angle with regard to a cone spreading from the camera lens
- Compare the objects from the current image with those from a previous and attempt to match them. If the objects are approaching, I would expect their proportions to change and internal angles to skew so I am not certain that rectangular detection would work best
- If an object is approaching, sound an alert and/or flash a signal.
I have no previous experience with the H7 and have some questions:
- What would be the best object detection method? I have been looking at Rectangular, Circular, and Blobs.
- Can the IO pins source enough current to drive a speaker or piezo buzzer or would I need to add a buffer to drive them?
- What would be the best method for matching objects detected from previous iterations?