updated README

README.md

@@ -7,27 +7,30 @@
 </p>
 <p align="center"><em><strong>Our Presentation (December 2020)</strong></em></p>
 
-## Members:
+## Members
 
 - Andrew Darling
 - Eric Hayes
 - Mehmet Yilmaz
 
-## About:
+## About
 
 - Given a skeleton based dataset collected from a depth sensor, the goal is to classify certain human actions using the Moving Pose algorithm as well as provide a simple UI.
 - To achieve this goal, we implmented the Moving Pose algorithm from the paper stated below and the database stated below.
 - This is our Fall 2020 CSCI470 (Introduction to Machine Learning) final Project. CSCI470 is an undergraduate class provided at the Colorado School of Mines. Our team name was: Nestlé.
 - Please view /movingpose/gui/README.md to learn more about the GUI and the hardware(s) used.
-- You can grab the weights used in the presentation/demo here: https://github.com/MehmetMHY/moving-pose/releases/tag/weights
 
-## Paper Implemented:
+## Weights
+
+The weights used in our implementation of Moving-Pose can be downloaded from [HERE](https://github.com/MehmetMHY/moving-pose/releases/tag/weights). These weights were tuned using cloud GPUs back in December 2020 and are the same weights used in the presentation/demo.
+
+## Paper Implemented
 
 - **Title:** _The Moving Pose: An Efficient 3D Kinematics Descriptor for Low-Latency Action Recognition and Detection_
 - **Authors:** Mihai Zanfir, Marius Leordeanu, & Cristian Sminchisescu.
 - **Paper:** [Zanfir_The_Moving_Pose_2013_ICCV_paper.pdf](https://openaccess.thecvf.com/content_iccv_2013/papers/Zanfir_The_Moving_Pose_2013_ICCV_paper.pdf)
 
-## Dataset Used:
+## Dataset Used
 
 - We used the MSR DailyActivity 3D Dataset dataset: [Dataset_Source](https://wangjiangb.github.io/my_data.html)
 - Multiview Action 3D Dataset Action IDs: