of the algorithm including execution on the GPU. The aim is also to
modify the code according to the PRedictable Execution Model (PREM).
-Stable version of the tracker is available from [CTU server][2],
-development happens at [GitHub][3].
+Stable version of the tracker is available from a [CTU server][2],
+development happens at GitHub [here][wsh] and [here][3].
[1]: http://hercules2020.eu/
[2]: http://rtime.felk.cvut.cz/gitweb/hercules2020/kcf.git
+[wsh]: https://github.com/wentasah/kcf
[3]: https://github.com/Shanigen/kcf
## Prerequisites
| --visualize, -v[delay_ms] | Visualize the output, optionally with specified delay. If the delay is 0 the program will wait for a key press. |
| --output, -o <output.txt> | Specify name of output file. |
| --debug, -d | Generate debug output. |
-| --fit, -f[W[xH]] | Specifies the dimension to which the extracted patch should be scaled. It should be divisible by 4. No dimension is the same as `128x128`, a single dimension `W` will result in patch size of `W`×`W`. |
+| --fit, -f[W[xH]] | Specifies the dimension to which the extracted patch should be scaled. It should be divisible by 4. No dimension or zero rounds the dimensions to the nearest smaller power of 2, a single dimension `W` will result in patch size of `W`×`W`. |
## Authors
Original C++ implementation of KCF tracker was written by Tomas Vojir
[here][12] and is reimplementation of algorithm presented in
-"High-Speed Tracking with Kernelized Correlation Filters" paper [1].
+"High-Speed Tracking with Kernelized Correlation Filters" paper \[1].
[12]: https://github.com/vojirt/kcf/blob/master/README.md
## References
-[1] João F. Henriques, Rui Caseiro, Pedro Martins, Jorge Batista,
+\[1] João F. Henriques, Rui Caseiro, Pedro Martins, Jorge Batista,
“High-Speed Tracking with Kernelized Correlation Filters“, IEEE
Transactions on Pattern Analysis and Machine Intelligence, 2015