Human motion synthesis using Unity3D

Overview

Human motion synthesis using Unity3D

Prerequisite:

Software: amc2bvh.exe, Unity 2017, Blender.
Unity: RockVR (Video Capture), scenes, character models Files:
Motion files: amc, asf or bvh formats.
Character models: fbx format.

Procedure

  1. If motion files in amc/asf format, run amc2bvh.exe to convert them to bvh
  2. Place all bvh files into "Desktop/New folder/bvh" (or modify script)
  3. Open Blender and run the bvh2fbx.py script. It will convert the motion files to fbx format which Unity can process and place them under the unity "Resources/Input"[1]
  4. Find the imported motion file in Unity and change its Animation Type to Humanoid under Rig. Check to make sure the model is mapped properly.
  5. Configure the different variations to record video (characters, camera angle, scene, lighting)
    1. For characters, add[2] or remove from the "characters" GameObject in Unity Editor for the ones desired. For new character added to the scene, add the "New Animation Controller"[3] in Asset to the character's controller in the "Animator" section.
    2. For camera, change the position of the DedicatedCapture GameObjects to the desired location. Add additional DedicatedCapture GameObjects for more angle. Read the documentation for RockVR Video Capture for more detail.
    3. For scene, check the desired scenes within the intro scene and run.
    4. For lighting, change the "lights" parameter in Automation.cs script. Add more values to the array for more variations in lighting angles.
  6. Start up the "intro" scene and run it from Unity Editor. Click "Start" button to start the problem.
  7. Adjust the desired resolution and framerate and click start. For initial run, leave all the counters to 0. For continuing runs enter the counters where the previous run left off. The videos will be recorded to "Documents/RockVR/Video"[4]

Note

  • [1] Converting too many bvh files at a time may result in Blender crashing. Try converting them in batches of smaller quantity (~50).
  • [2] To add a GameObject to a Scene in Unity, drag it from the Asset menu to a position in the Hierarchy menu or a position in the scene itself. You can also create an empty GameObject from the "GameObject->Create Empty" option.
  • [3] Depending on the framerate of the motion files, you may need to adjust the speed of the animation. To do this go to "Assets" and find the "New Animator Controller" and open it. Then click on "New State" and adjust the speed to framerate/24 (if 120 frames changes to 5, if 60 change to 2.5, etc). Also find the line "timeLeft = ((AnimationClip)clips[clipCounter]).length;" in the SwitchAnimation function and divide it by the speed.
  • [4] Unity will most likely freeze or crash if left running for too long. Adjust the counters in the "intro" scene to resume progress.

Scene Creation procedure

  1. To get a scene, either download a pre-built one or build one yourself using various 3d models for GameObjects.
  2. Create an empty GameObject named "characters" and place it at a location best suited for recording. Add a character to it to see if any adjusting or scaling is needed.
  3. Add DedicatedCapture GameObjects from the "RockVR/Video/Prefabs" folder to the scene in desired locations.
  4. Attach the AudioCapture script in "RockVR/Video/Scripts" folder to the main camera.
  5. Create an empty GameObject named "VideoCaptureCtrl" and attach the VideoCaptureCtrl script in "RockVR/Video/Scripts" to it. Also attach the Automation.cs script from "Scripts" to it as well.
  6. Add the first DedicatedCapture GameObject as well as the AudioCapture to the the VideoCaptureCtrl script.
  7. If there is no "Directional light" GameObject, create one.
  8. Add the created scene to build settings.
  9. Add a check box in the intro scene for the newly created scene and modify the scene "ProcessParameter" accordingly.

Additional characters

In the "characters" folder in Assets, there is a list of preprocessed characters I got from the Unity asset store for free.
To process new characters:

  1. Change its Animation type to Humanoid under Rig
  2. Fix any mapping problem for the bones of the character
  3. Remove the mapping on the bones for both hands. This could be done using the "New Human Template" in the Assets folder. (This is to avoid weird finger mapping from the animations)

Instructions on error handling

  • If you tried to terminate the program insider the Unity Editor, the ffmpeg.exe will still be running and result in unfinished video and audio files to remain in the videos folder. To solve this issue, simply terminate the ffmpeg.exe from task manager and delete the unfinished files.
  • Since the program freezes fairly often, a temporary save state feature is implemented. Once Unity froze, terminate it from task manager. Look into the videos folder and figure out what combination the next video should be. Enter the parameters where the last run left off in the "intro" scene (various counters) to pick up from there.

Local environment specs

  • OS: Microsoft Windows 10 Pro
  • Version: 10.0.16299 Build 16299
  • Processor: Intel(R) Xeon(R) CPU E5-2630 v4 @ 2.20GHz, 2201 Mhz, 10 Core(s), 20 Logical Processor(s)
  • Total Physical Memory: 63.9 GB
  • GPU: NVIDIA Quadro M5000
Owner
Hao Xu
Hao Xu
SCALE: Modeling Clothed Humans with a Surface Codec of Articulated Local Elements (CVPR 2021)

SCALE: Modeling Clothed Humans with a Surface Codec of Articulated Local Elements (CVPR 2021) This repository contains the official PyTorch implementa

Qianli Ma 133 Jan 05, 2023
O2O-Afford: Annotation-Free Large-Scale Object-Object Affordance Learning (CoRL 2021)

O2O-Afford: Annotation-Free Large-Scale Object-Object Affordance Learning Object-object Interaction Affordance Learning. For a given object-object int

Kaichun Mo 26 Nov 04, 2022
Rethinking Nearest Neighbors for Visual Classification

Rethinking Nearest Neighbors for Visual Classification arXiv Environment settings Check out scripts/env_setup.sh Setup data Download the following fin

Menglin Jia 29 Oct 11, 2022
Curvlearn, a Tensorflow based non-Euclidean deep learning framework.

English | 简体中文 Why Non-Euclidean Geometry Considering these simple graph structures shown below. Nodes with same color has 2-hop distance whereas 1-ho

Alibaba 123 Dec 12, 2022
Get the partition that a file belongs and the percentage of space that consumes

tinos_eisai_sy Get the partition that a file belongs and the percentage of space that consumes (works only with OSes that use the df command) tinos_ei

Konstantinos Patronas 6 Jan 24, 2022
Official repository for the paper "Self-Supervised Models are Continual Learners" (CVPR 2022)

Self-Supervised Models are Continual Learners This is the official repository for the paper: Self-Supervised Models are Continual Learners Enrico Fini

Enrico Fini 73 Dec 18, 2022
MegEngine implementation of YOLOX

Introduction YOLOX is an anchor-free version of YOLO, with a simpler design but better performance! It aims to bridge the gap between research and ind

旷视天元 MegEngine 77 Nov 22, 2022
Official Pytorch implementation of RePOSE (ICCV2021)

RePOSE: Iterative Rendering and Refinement for 6D Object Detection (ICCV2021) [Link] Abstract We present RePOSE, a fast iterative refinement method fo

Shun Iwase 68 Nov 15, 2022
Code for our paper "Graph Pre-training for AMR Parsing and Generation" in ACL2022

AMRBART An implementation for ACL2022 paper "Graph Pre-training for AMR Parsing and Generation". You may find our paper here (Arxiv). Requirements pyt

xfbai 60 Jan 03, 2023
3D dataset of humans Manipulating Objects in-the-Wild (MOW)

MOW dataset [Website] This repository maintains our 3D dataset of humans Manipulating Objects in-the-Wild (MOW). The dataset contains 512 images in th

Zhe Cao 28 Nov 06, 2022
Genpass - A Passwors Generator App With Python3

Genpass Welcom again into another python3 App this is simply an Passwors Generat

Mal4D 1 Jan 09, 2022
A rule learning algorithm for the deduction of syndrome definitions from time series data.

README This project provides a rule learning algorithm for the deduction of syndrome definitions from time series data. Large parts of the algorithm a

0 Sep 24, 2021
Real-world Anomaly Detection in Surveillance Videos- pytorch Re-implementation

Real world Anomaly Detection in Surveillance Videos : Pytorch RE-Implementation This repository is a re-implementation of "Real-world Anomaly Detectio

seominseok 62 Dec 08, 2022
Reusable constraint types to use with typing.Annotated

annotated-types PEP-593 added typing.Annotated as a way of adding context-specific metadata to existing types, and specifies that Annotated[T, x] shou

125 Dec 26, 2022
Optimized primitives for collective multi-GPU communication

NCCL Optimized primitives for inter-GPU communication. Introduction NCCL (pronounced "Nickel") is a stand-alone library of standard communication rout

NVIDIA Corporation 2k Jan 09, 2023
This is the official implementation for the paper "(Almost) Free Incentivized Exploration from Decentralized Learning Agents" in NeurIPS 2021.

Observe then Incentivize Experiments This is the code used for the paper "(Almost) Free Incentivized Exploration from Decentralized Learning Agents",

Cong Shen Research Group 0 Mar 08, 2022
pytorch implementation of Attention is all you need

A Pytorch Implementation of the Transformer: Attention Is All You Need Our implementation is largely based on Tensorflow implementation Requirements N

230 Dec 07, 2022
AI Based Smart Exam Proctoring Package

AI Based Smart Exam Proctoring Package It takes image (base64) as input: Provide Output as: Detection of Mobile phone. Detection of More than 1 person

NARENDER KESWANI 3 Sep 09, 2022
Recommendationsystem - Movie-recommendation - matrixfactorization colloborative filtering recommendation system user

recommendationsystem matrixfactorization colloborative filtering recommendation

kunal jagdish madavi 1 Jan 01, 2022