Computes normalized LBP histogram, averaged over frames of the video
Forked from ivana7c/calclbp/1
Algorithms have at least one input and one output. All algorithm endpoints are organized in groups. Groups are used by the platform to indicate which inputs and outputs are synchronized together. The first group is automatically synchronized with the channel defined by the block in which the algorithm is deployed.
Parameters allow users to change the configuration of an algorithm when scheduling an experiment
|radius||LBP radius in pixels||uint32||1|
|num-neighbors||Number of points to be used for the LBP operator||uint32||8|
The code for this algorithm in Python
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This algorithm computes LBP-based feature vector. For a given input set of frames in a video, it computes the normalized LBP histogram. Then, it computes the final feature vector on video level, by averaging the normalized LBP histograms.
The used LBP operator is computed over a circular neighborhood and is uniform. Details about LBP operator can be found in [Ojala02]
This algorithm relies on the Bob library.
|[Ojala02]||Ojala, Pietikainen and Maenpaa: Multiresolution gray-scale and rotation invariant texture classification with Local Binary Patterns. IEEE Transactions on Pattern Analysis and Machine inteligence 2002|
This table shows the number of times this algorithm has been successfully run using the given environment. Note this does not provide sufficient information to evaluate if the algorithm will run when submitted to different conditions.