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Merge branch 'master' of https://web.gin.g-node.org/ioannis.agtzidis/gazecom_annotations

Ioannis Agtzidis il y a 4 ans
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      README.md

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README.md

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 We also provide the annotations from our algorithm as detected from the
 We also provide the annotations from our algorithm as detected from the
 [sp\_tool](https://github.com/MikhailStartsev/sp_tool), which is based on
 [sp\_tool](https://github.com/MikhailStartsev/sp_tool), which is based on
 Agtzidis et al. (2016), along with annotations from Berg et al. (2009) and Larsson et al.
 Agtzidis et al. (2016), along with annotations from Berg et al. (2009) and Larsson et al.
-(2015) in the corresponding folders starting with *output_*.
+(2015) (our re-implementation of the latter is available on the http://michaeldorr.de/smoothpursuit/ page, or via this [link](http://michaeldorr.de/smoothpursuit/larsson_reimplementation.zip)) in the corresponding folders starting with *output_*.
 
 
 Finally, a collection of 45 hand annotated targets is provided in the 
 Finally, a collection of 45 hand annotated targets is provided in the 
 [targets\_arff](https://web.gin.g-node.org/ioannis.agtzidis/gazecom_annotations/src/master/targets_arff)
 [targets\_arff](https://web.gin.g-node.org/ioannis.agtzidis/gazecom_annotations/src/master/targets_arff)
@@ -25,10 +25,17 @@ folder.
 
 
 # sp_tool
 # sp_tool
 
 
-The implementation of our detection algorithm together with a wide variety of
+The implementation of our clustering-based detection algorithm together with a wide variety of
 evaluation metrics for eye movement classification can be found 
 evaluation metrics for eye movement classification can be found 
 [here](https://github.com/MikhailStartsev/sp_tool).
 [here](https://github.com/MikhailStartsev/sp_tool).
 
 
+# Model performance comparison
+A tentative evaluation table of sample-level model evaluation statistics for eye movement classification on GazeCom is available at http://michaeldorr.de/smoothpursuit/.
+
+For a more thorough evaluation (all eye movement classes; including event-level metrcis), plese refer to our later papers:
+* [1D CNN with BLSTM for automated classification of fixations, saccades, and smooth pursuits](https://link.springer.com/article/10.3758/s13428-018-1144-2) (Startsev et al., 2019, Behavior Research Methods).
+* [A novel gaze event detection metric that is not fooled by gaze-independent baselines](https://dl.acm.org/citation.cfm?id=3319836) (Startsev et al., 2019, ETRA)
+
 ## References
 ## References
 
 
 Agtzidis, I., Startsev, M., & Dorr, M. (2016). Smooth pursuit detection
 Agtzidis, I., Startsev, M., & Dorr, M. (2016). Smooth pursuit detection