Comments (4)
Could we use transitions for more efficiently move the prediction location?
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I've done some profiling with Google Chrome's profiler. Most of the bottlenecks where in clmtrakr as expected. One potential area of optimization is the LUDecomposition in the mat.js file as that was taking up a significant fraction of the execution time.
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Here are the three prime spots for optimization that I have identified:
- The ridge() method and it's submethod is probably our best bet for improved performance.
- track() inside of CLMR tracker
- getPupilFeatures() and it's methods in CLMGaze is also in need of potential optimization.
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Performance improved in a7962dc
At this point, we're at a local limit of what we think we can improve performance-wise. Please open a new issue with specific ideas for improving the performance.
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Related Issues (20)
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