Datasets:
Tasks:
Other
Languages:
English
Multilinguality:
monolingual
Size Categories:
10K<n<100K
Language Creators:
expert-generated
Annotations Creators:
expert-generated
Source Datasets:
original
Tags:
head-pose-estimation
License:
File size: 10,110 Bytes
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---
annotations_creators:
- expert-generated
language_creators:
- expert-generated
language:
- en
license:
- other
multilinguality:
- monolingual
pretty_name: Biwi Kinect Head Pose Database
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- other
task_ids: []
paperswithcode_id: biwi
tags:
- head-pose-estimation
dataset_info:
features:
- name: sequence_number
dtype: string
- name: subject_id
dtype: string
- name: rgb
sequence: image
- name: rgb_cal
struct:
- name: intrisic_mat
dtype:
array2_d:
shape:
- 3
- 3
dtype: float64
- name: extrinsic_mat
struct:
- name: rotation
dtype:
array2_d:
shape:
- 3
- 3
dtype: float64
- name: translation
sequence: float64
length: 3
- name: depth
sequence: string
- name: depth_cal
struct:
- name: intrisic_mat
dtype:
array2_d:
shape:
- 3
- 3
dtype: float64
- name: extrinsic_mat
struct:
- name: rotation
dtype:
array2_d:
shape:
- 3
- 3
dtype: float64
- name: translation
sequence: float64
length: 3
- name: head_pose_gt
sequence:
- name: center
sequence: float64
length: 3
- name: rotation
dtype:
array2_d:
shape:
- 3
- 3
dtype: float64
- name: head_template
dtype: string
splits:
- name: train
num_bytes: 6914063
num_examples: 24
download_size: 6014398431
dataset_size: 6914063
---
# Dataset Card for Biwi Kinect Head Pose Database
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-instances)
- [Data Splits](#data-instances)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Source Data](#source-data)
- [Annotations](#annotations)
- [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
- [Social Impact of Dataset](#social-impact-of-dataset)
- [Discussion of Biases](#discussion-of-biases)
- [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
- [Dataset Curators](#dataset-curators)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
## Dataset Description
- **Homepage:** [Biwi Kinect Head Pose homepage](https://icu.ee.ethz.ch/research/datsets.html)
- **Repository:** [Needs More Information]
- **Paper:** [Biwi Kinect Head Pose paper](https://link.springer.com/article/10.1007/s11263-012-0549-0)
- **Leaderboard:** [Needs More Information]
- **Point of Contact:** [Gabriele Fanelli](mailto:gabriele.fanelli@gmail.com)
### Dataset Summary
The Biwi Kinect Head Pose Database is acquired with the Microsoft Kinect sensor, a structured IR light device.It contains 15K images of 20 people with 6 females and 14 males where 4 people were recorded twice.
For each frame, there is :
- a depth image,
- a corresponding rgb image (both 640x480 pixels),
- annotation
The head pose range covers about +-75 degrees yaw and +-60 degrees pitch. The ground truth is the 3D location of the head and its rotation.
### Data Processing
Example code for reading a compressed binary depth image file provided by the authors.
<details>
<summary> View C++ Code </summary>
```cpp
/*
* Gabriele Fanelli
*
* fanelli@vision.ee.ethz.ch
*
* BIWI, ETHZ, 2011
*
* Part of the Biwi Kinect Head Pose Database
*
* Example code for reading a compressed binary depth image file.
*
* THE SOFTWARE IS PROVIDED “AS IS” AND THE PROVIDER GIVES NO EXPRESS OR IMPLIED WARRANTIES OF ANY KIND,
* INCLUDING WITHOUT LIMITATION THE WARRANTIES OF FITNESS FOR ANY PARTICULAR PURPOSE AND NON-INFRINGEMENT.
* IN NO EVENT SHALL THE PROVIDER BE HELD RESPONSIBLE FOR LOSS OR DAMAGE CAUSED BY THE USE OF THE SOFTWARE.
*
*
*/
#include <iostream>
#include <fstream>
#include <cstdlib>
int16_t* loadDepthImageCompressed( const char* fname ){
//now read the depth image
FILE* pFile = fopen(fname, "rb");
if(!pFile){
std::cerr << "could not open file " << fname << std::endl;
return NULL;
}
int im_width = 0;
int im_height = 0;
bool success = true;
success &= ( fread(&im_width,sizeof(int),1,pFile) == 1 ); // read width of depthmap
success &= ( fread(&im_height,sizeof(int),1,pFile) == 1 ); // read height of depthmap
int16_t* depth_img = new int16_t[im_width*im_height];
int numempty;
int numfull;
int p = 0;
while(p < im_width*im_height ){
success &= ( fread( &numempty,sizeof(int),1,pFile) == 1 );
for(int i = 0; i < numempty; i++)
depth_img[ p + i ] = 0;
success &= ( fread( &numfull,sizeof(int), 1, pFile) == 1 );
success &= ( fread( &depth_img[ p + numempty ], sizeof(int16_t), numfull, pFile) == (unsigned int) numfull );
p += numempty+numfull;
}
fclose(pFile);
if(success)
return depth_img;
else{
delete [] depth_img;
return NULL;
}
}
float* read_gt(const char* fname){
//try to read in the ground truth from a binary file
FILE* pFile = fopen(fname, "rb");
if(!pFile){
std::cerr << "could not open file " << fname << std::endl;
return NULL;
}
float* data = new float[6];
bool success = true;
success &= ( fread( &data[0], sizeof(float), 6, pFile) == 6 );
fclose(pFile);
if(success)
return data;
else{
delete [] data;
return NULL;
}
}
```
</details>
### Supported Tasks and Leaderboards
Biwi Kinect Head Pose Database supports the following tasks :
- Head pose estimation
- Pose estimation
- Face verification
### Languages
[Needs More Information]
## Dataset Structure
### Data Instances
A sample from the Biwi Kinect Head Pose dataset is provided below:
```
{
'sequence_number': '12',
'subject_id': 'M06',
'rgb': [<PIL.PngImagePlugin.PngImageFile image mode=RGB size=640x480 at 0x7F53A6446C10>,.....],
'rgb_cal':
{
'intrisic_mat': [[517.679, 0.0, 320.0], [0.0, 517.679, 240.5], [0.0, 0.0, 1.0]],
'extrinsic_mat':
{
'rotation': [[0.999947, 0.00432361, 0.00929419], [-0.00446314, 0.999877, 0.0150443], [-0.009228, -0.015085, 0.999844]],
'translation': [-24.0198, 5.8896, -13.2308]
}
}
'depth': ['../hpdb/12/frame_00003_depth.bin', .....],
'depth_cal':
{
'intrisic_mat': [[575.816, 0.0, 320.0], [0.0, 575.816, 240.0], [0.0, 0.0, 1.0]],
'extrinsic_mat':
{
'rotation': [[1.0, 0.0, 0.0], [0.0, 1.0, 0.0], [0.0, 0.0, 1.0]],
'translation': [0.0, 0.0, 0.0]
}
}
'head_pose_gt':
{
'center': [[43.4019, -30.7038, 906.864], [43.0202, -30.8683, 906.94], [43.0255, -30.5611, 906.659], .....],
'rotation': [[[0.980639, 0.109899, 0.162077], [-0.11023, 0.993882, -0.00697376], [-0.161851, -0.011027, 0.986754]], ......]
}
}
```
### Data Fields
- `sequence_number` : This refers to the sequence number in the dataset. There are a total of 24 sequences.
- `subject_id` : This refers to the subjects in the dataset. There are a total of 20 people with 6 females and 14 males where 4 people were recorded twice.
- `rgb` : List of png frames containing the poses.
- `rgb_cal`: Contains calibration information for the color camera which includes intrinsic matrix,
global rotation and translation.
- `depth` : List of depth frames for the poses.
- `depth_cal`: Contains calibration information for the depth camera which includes intrinsic matrix, global rotation and translation.
- `head_pose_gt` : Contains ground truth information, i.e., the location of the center of the head in 3D and the head rotation, encoded as a 3x3 rotation matrix.
### Data Splits
All the data is contained in the training set.
## Dataset Creation
### Curation Rationale
[More Information Needed]
### Source Data
#### Initial Data Collection and Normalization
The Biwi Kinect Head Pose Database is acquired with the Microsoft Kinect sensor, a structured IR light device.
#### Who are the source language producers?
[More Information Needed]
### Annotations
#### Annotation process
From Dataset's README :
> The database contains 24 sequences acquired with a Kinect sensor. 20 people (some were recorded twice - 6 women and 14 men) were recorded while turning their heads, sitting in front of the sensor, at roughly one meter of distance.
#### Who are the annotators?
[More Information Needed]
### Personal and Sensitive Information
[More Information Needed]
## Considerations for Using the Data
### Social Impact of Dataset
[More Information Needed]
### Discussion of Biases
[More Information Needed]
### Other Known Limitations
[More Information Needed]
## Additional Information
### Dataset Curators
[Needs More Information]
### Licensing Information
From Dataset's README :
> This database is made available for non-commercial use such as university research and education.
### Citation Information
```bibtex
@article{fanelli_IJCV,
author = {Fanelli, Gabriele and Dantone, Matthias and Gall, Juergen and Fossati, Andrea and Van Gool, Luc},
title = {Random Forests for Real Time 3D Face Analysis},
journal = {Int. J. Comput. Vision},
year = {2013},
month = {February},
volume = {101},
number = {3},
pages = {437--458}
}
```
### Contributions
Thanks to [@dnaveenr](https://github.com/dnaveenr) for adding this dataset. |