X-Git-Url: http://rtime.felk.cvut.cz/gitweb/hercules2020/kcf.git/blobdiff_plain/435ce10fdd459c9e95b2fb10545710ba28029ff4..HEAD:/README.md

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 # KCF tracker – parallel and PREM implementations
 
 The goal of this project is modify KCF tracker for use in the
-[HERCULES][1] project, where it will run on NVIDIA TX2 board. To
-achieve the needed performance we try various ways of parallelization
-of the algorithm including execution on the GPU. The aim is also to
-modify the code according to the PRedictable Execution Model (PREM).
+[HERCULES][1] project, where it will run on NVIDIA TX2 board. The
+differences from the [original version][orig] are:
+  * To achieve the needed performance on TX2, we try various ways of
+    parallelizing the algorithm, including execution on the GPU.
+  * The tracker is extended to track rotating objects.
+  * The aim is also to modify the code to comply with the PRedictable
+    Execution Model (PREM).
 
 Stable version of the tracker is available from a [CTU server][2],
 development happens at [GitHub][iig].
@@ -13,6 +16,7 @@ development happens at [GitHub][iig].
 [2]: http://rtime.felk.cvut.cz/gitweb/hercules2020/kcf.git
 [iig]: https://github.com/CTU-IIG/kcf
 [3]: https://github.com/Shanigen/kcf
+[orig]: https://github.com/vojirt/kcf
 
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 **Table of Contents**
@@ -176,14 +180,14 @@ top_left_y, width, height".
 | --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. |
-| --visual_debug, -p[p|r] | Show graphical window with debugging information (either **p**atch or filter **r**esponse). |
+| --visual_debug, -p[p\|r] | Show graphical window with debugging information (either **p**atch or filter **r**esponse). |
 
 ## Automated testing
 
 The tracker comes with a test suite based on [vot2016 datatset][11].
 You can run the test suite as follows:
 
-    make vot2016  # This download the datased (about 1GB of data)
+    make vot2016  # This downloads the dataset (about 1GB of data)
 	make test
 
 The above command run all tests in parallel and displays the results