Object Detection without Classifiers

asked 2015-12-30 18:13:37 -0500

Sqzr gravatar image

I am attempting to crude application that identifies features or objects from a video stream, detects feature contours, attempts to group contours into separate objects and determines the depth of each contour point.

Being new to OpenCV I am unaware of the numerous techniques/approaches/algorithms I could use to achieve this. Given my order of operations below can you suggest OpenCV techniques/approaches/algorithms to use. I can then look further into these and learn along the way.

Order of Operations (I've elaborated on the techniques I know so far to use; please let me know of better and alternative techniques):

  • Read video stream
  • Identify contours: Apply gaussian blur to reduce noise, call findContours()
  • Classify objects: Inspect contours and identify which contours belong to which object. Any advice for this approach
  • For each contour point: determine the depth of this point. Any advice for this approach
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what might "depth of each contour point." mean ?

berak gravatar imageberak ( 2015-12-30 22:18:05 -0500 )edit

@berak thanks for your comment, I mean if its possible to determine the depth/distance of the point from the camera. At the least figure out which object is relatively in front of another from the camera's perspective.

Sqzr gravatar imageSqzr ( 2015-12-30 22:40:21 -0500 )edit