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Supplementary material for the CVPR'09 submission "Dense saliency-based spatiotemporal feature points for action recognition"
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---------- CONTENTS ----------------------------
The zip file contains example images and videos for the two action datasets refered in the manuscript, namely the KTH and HOHA datasets.


	--------- IMAGES 
	The images are in png format and show the detected cuboids on all frames of the clip as a stack of images.


	--------- VIDEOS 
	The videos are encoded with the DivX 6.8.5 codec that can be downloaded from http://www.divx.com/divx/windows/codec/.
	They are vetically split into two parts: the upper part shows the detected cuboids on the depicted action, while the lower part shows the saliency response computed by our algorithm.

 
---------- DIRECTORY STRUCTURE ------------------
The directory and filenames are self-explanatory. Images & videos are divided according to the datasets and the action they belong to. 


	---------- HOHA dataset
	There are 8 sub-directories that correspond to each of the 8 involved actions.

		--- Example
		dir:	"HOHA_dataset-->answerPhone"
		files: 	"answer_phone_Dead_Poets_1741_points.png", "answer_phone_Dead_Poets_1741_points_merged.avi"
		action: "answerPhone"
		clip:	"Dead_Poets_1741.avi"


	--------- KTH dataset
	There are 6 sub-directories that correspond to each of the 6 involved actions. Each sub-directory contains 4 images and videos. One for each of the 4 scenarios (see dataset description in the manuscript).

		--- Example
		dir:		"KTH_dataset-->handwaving"
		files:		"points_person03_handwaving_s1.png","points_person03_handwaving_s1_merged.avi"
		action:		"handwaving"
		person:		"03" (see dataset description in the manuscript)
		scenario:	"s1" (see dataset description in the manuscript)





