Datasets:

ETHZurich
/

biwi_kinect_head_pose

	---
	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.