CODEWITHSUNDEEP
performanceopencvopticalflow
Danilo Carvalho
Danilo Carvalho

Reputation: 395

Faster alternatives for calcOpticalFlowSF

Is there any faster alternatives for calcOpticalFlowSF? Its just sooo slow and wanna run this thing with a sequence of frames coming from a video. How can I do that?

Upvotes: 2

Views: 2653

Answers (1)

Tobias Senst
Tobias Senst

Reputation: 2830

There several methods for optical flow based motion estimation but you have to consider several things:

  • are you restricted to CPU implementation / GPU's implementation could decrease drastically the run-time
  • do you need dense motion fields or just a set of sparse motion vectors / sparse OF methods are more scalable and thus need less run-time
  • accuracy / the very high accuracy of dense methods is most only critical on motion boundaries. In many application you could approximate a dense motion field by a grid of sparse motion vectors and thus can use sparse methods as the pyramidal Lucas Kanade (OpenCV)

current libaries / methods are:

Dense Methods:

  • OpenCV 2.4.4 provides on GPU BroxOpticalFlow that is fast too
  • the FlowLib of the GPU4Vision Group provides a high accurate GPU implementation
  • GPU implementation of the TV-L1 on GPU is provided by

Sparse Methods:

  • OpenCV since 2.4.2 provides the pyramidal Lucas Kanade on GPU /earlier verions also very fast implementation on the CPU
  • the RLOFLib provides an more accurate implementation for GPU / CPU and Matlab
  • the Gain Adaptive Lucas Kanade / KLT is also available for GPU

You could also take a look to the current Optical Flow benchmarks, where the researcher sometimes provides Link. Common Optical Flow benchmarks are the Middlebury and the KITTI

Upvotes: 5

Related Questions