What is h36m Dataset and Why You Need It for 3D Human Modeling
If you are interested in 3D human pose estimation, you might have heard of the term "h36m download". But what does it mean and why is it important? In this article, we will explain what h36m download is, how it can help you with 3D human pose estimation, and how to get it. We will also show you how to set up, use, and evaluate the Human3.6M dataset, which is one of the largest and most widely used datasets for 3D human pose estimation. Finally, we will discuss some of the challenges and limitations of the Human3.6M dataset and suggest some future directions and recommendations.
What is h36m download?
H36m download is a shorthand for downloading the Human3.6M dataset, which is a large-scale motion capture dataset that contains 3.6 million human poses and corresponding images captured by a high-speed motion capture system . The dataset covers 11 professional actors performing 17 scenarios, such as discussion, smoking, taking photo, talking on the phone, etc. The dataset provides accurate 3D joint positions and joint angles from a high-speed motion capture system, as well as high-resolution videos from 4 calibrated cameras . The dataset also provides pixel-level 24 body part labels for each configuration, time-of-flight range data, 3D laser scans of the actors, accurate background subtraction, person bounding boxes, precomputed image descriptors, software for visualization and prediction, and performance evaluation on a withheld test set .
Why is it useful for 3D human pose estimation?
3D human pose estimation is a computer vision task that involves estimating the 3D positions and orientations of body joints and bones from 2D images or videos . It has widespread applications in various areas, such as virtual reality, human-computer interaction, robots, motion analysis, etc. However, it is a challenging task due to depth ambiguities and the lack of in-the-wild datasets . Therefore, having a large-scale, accurate, and diverse dataset like Human3.6M can greatly facilitate the research and development of 3D human pose estimation methods.
The Human3.6M dataset is one of the largest motion capture datasets available for 3D human pose estimation . It provides a rich source of data for training and testing different models and algorithms. It also enables the comparison and evaluation of different methods on a common benchmark. Moreover, the Human3.6M dataset covers a wide range of human activities and poses that can be used to study various aspects of human motion, such as dynamics, kinematics, interactions, etc.
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How to get it?
To get the Human3.6M dataset, you need to register to the Human3.6M website (or login if you already have an account) and download the dataset in its original format or preprocessed format. You can also use some scripts or tools to fetch or convert the dataset to your desired format . We will explain more about how to set up the Human3.6M dataset in the next section.
How to set up the Human3.6M dataset?
There are two ways to set up the Human3.6M dataset on your pipeline: setup from original source or setup from preprocessed dataset. The two methods produce the same result, but have different steps and requirements. We will compare and contrast the two methods in the following subsections.
Setup from original source (recommended)
This method involves downloading the original Human3.6M dataset from the website and converting it to your desired format using some scripts or tools. This method is recommended because it gives you the most flexibility and control over the data quality and format. However, it also requires more steps and resources than the other method.
Steps and requirements
To set up the Human3.6M dataset from the original source, you need to follow these steps:
Register to the Human3.6M website (or login if you already have an account) and agree to the terms and conditions.
Download the dataset files from the website . The dataset consists of 3.6 million poses in .cdf format, 4 videos per subject per action in .mp4 format, and 24 body part labels per subject per action in .mat format. The total size of the dataset is about 312 GB.
Extract the downloaded files to your local directory. You can use tools like 7-Zip or WinRAR to unzip the files.
Convert the .cdf files to .mat files using a script or tool like cdf2mat or h36m_cdf2mat . This step is necessary because most of the existing codebases for 3D human pose estimation use .mat files as input.
Convert the .mat files to your desired format using a script or tool like h36m_mat2h5 or h36m_mat2npz . This step is optional but recommended because it can reduce the file size and improve the loading speed of the data.
Organize the converted files into a suitable directory structure for your pipeline. You can use a script or tool like h36m_organize or h36m_preprocess to automate this step.
Advantages and disadvantages
The advantages of setting up the Human3.6M dataset from the original source are:
You can get the most complete and accurate version of the dataset, without any loss of information or quality.
You can choose your preferred format and resolution for the data, depending on your needs and preferences.
You can customize and modify the data as you wish, such as cropping, resizing, augmenting, etc.
The disadvantages of setting up the Human3.6M dataset from the original source are:
You need to download a large amount of data, which can take a long time and consume a lot of bandwidth and storage space.
You need to convert and organize the data, which can be tedious and time-consuming, especially if you are not familiar with the scripts or tools.
You need to have access to a powerful computer with enough memory and processing power to handle the data conversion and manipulation.
Setup from preprocessed dataset (old instructions)
This method involves downloading a preprocessed version of the Human3.6M dataset from an external source and using it directly on your pipeline. This method is simpler and faster than the other method, but it also has some drawbacks and limitations.
Steps and requirements
To set up the Human3.6M dataset from the preprocessed dataset, you need to follow these steps:
Download the preprocessed dataset file from this link . The file is a .zip file that contains 17 .h5 files, one for each action in the Human3.6M dataset. The total size of the file is about 2 GB.
Extract the downloaded file to your local directory. You can use tools like 7-Zip or WinRAR to unzip the file.
Use the extracted .h5 files as input for your pipeline. You can use tools like h5py or PyTables to read and write .h5 files in Python.
Advantages and disadvantages
The advantages of setting up the Human3.6M dataset from the preprocessed dataset are:
You can download a smaller amount of data, which can save you time and space.
You can use the data directly without any conversion or organization, which can simplify your