Difference between revisions of "Full Body Pose Estimation for Sports Analysis"
m |
m |
||
| (4 intermediate revisions by the same user not shown) | |||
| Line 1: | Line 1: | ||
| + | <br> | ||
{{Ambox | {{Ambox | ||
|image=[[File:underconstruction.png|50px]] | |image=[[File:underconstruction.png|50px]] | ||
| Line 4: | Line 5: | ||
|issue='''WORK IN PROGRESS. Please [https://www.ridgerun.com/contact <U>Contact</U>] RidgeRun OR email to [mailto:support@ridgerun.com <u>support@ridgerun.com</u>] if you have any questions.''' | |issue='''WORK IN PROGRESS. Please [https://www.ridgerun.com/contact <U>Contact</U>] RidgeRun OR email to [mailto:support@ridgerun.com <u>support@ridgerun.com</u>] if you have any questions.''' | ||
}} | }} | ||
| + | <br> | ||
| + | <seo | ||
| + | title="Full Body Pose Estimation for Sports Analysis | RidgeRun" titlemode="replace" | ||
| + | metakeywords="GStreamer, Embedded Linux, Device Drivers, NVIDIA, nvidia jetson, Jetson, cuda, Tegra, Jetson AGX Xavier, Jetson Xavier, NVIDIA Jetson Xavier NX, Xavier NX, Jetson Xavier NX, NVIDIA Jetson Xavier, Xavier, Jetson Xavier NX Developer Kit, Jetson Nano, Nano, Jetson Nano 4GB devkit, Jetson Nano devkit, Jetson AGX Orin, Jetson AGX Orin devkit, orin, orin agx, Jetson Orin, Jetson Orin NX, NVIDIA Jetson Orin NX, Jetson AGX Orin, Orin AGX, Orin NX, TX1, TX2, Tegra TX1,Tegra TX2, Jetson TX2 NX, Embedded Linux driver development, Linux Software development, Embedded Linux SDK, Embedded Linux Application development, GStreamer Multimedia Framework, AI, Deep Learning, Connect Tech Astro Carrier Board, Connect Tech Astro, Astro Carrier Board, Leopard Imaging LI-OV10635-SER, LI-OV10635-SER,Body Pose Estimation, Pose Estimation, Sports Analysis, Jetson Nano, Jetson TX1, Jetson TX2, Full Body Pose Estimation, Camera Abstraction, Camera Calibration, AprilTag Camera Calibration, Chessboard Camera Calibration, 3D Pose Estimation, Pose Representation, Skeleton Calibration, Temporal Filter, Kinematic Fitting" metadescription="Learn about the Full Body Pose Estimation for Sports Analysis on NVIDIA Jetson platform in this RidgeRun developer wiki guide."> | ||
| + | </seo> | ||
| + | |||
| + | {{Full Body Pose Estimation for Sports Analysis/Foot|previous=|next=About}} | ||
<noinclude>{{DISPLAYTITLE:Full Body Pose Estimation for Sports Analysis|noerror}}</noinclude> | <noinclude>{{DISPLAYTITLE:Full Body Pose Estimation for Sports Analysis|noerror}}</noinclude> | ||
{{Full Body Pose Estimation for Sports Analysis/Main_contents}} | {{Full Body Pose Estimation for Sports Analysis/Main_contents}} | ||
| − | + | {{Full Body Pose Estimation for Sports Analysis/Foot|previous=|next=About}} | |
Latest revision as of 12:36, 26 April 2023
 | WORK IN PROGRESS. Please Contact RidgeRun OR email to support@ridgerun.com if you have any questions. |
|
Welcome to RidgeRun's Full Body |
||
|
Overview | ||
|
Pose estimation has become one of the topics of interest in the computer vision field. It constitutes a great method of interaction between computational systems and the real world. It is widely used in tasks such as biomedical motion analysis, sports analysis, or even as a motion capture technology to animate virtual characters. At RidgeRun we decided to take part, and we started our own research project based on three-dimensional human pose estimation. We developed a multi-view human 3D pose estimation system, which is constituted by two stages. In the first stage, we perform an initial estimation using the data provided by the camera system. Then, on the second stage, the initial pose estimation gets processed to assure bio-mechanical plausibility and temporal consistency. With a multi-camera setup as simple as the one shown in
the following image:
You will be able to estimate the three-dimensional pose of the user. Reaching great results as shown in our next video demonstration.
| ||
|
RidgeRun support | ||
|
RidgeRun provides support for Embedded Linux development, specializing in the use of hardware accelerators in multimedia applications. RidgeRun's products take full advantage of the accelerators exposed to perform transformations on the video streams achieving great performance on complex processing.
| ||
