metadata

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

Dataset Description
Dataset Structure
Dataset Creation
Considerations for Using the Data
Additional Information

Dataset Description

Homepage: Biwi Kinect Head Pose homepage
Repository: [Needs More Information]
Paper: Biwi Kinect Head Pose paper
Leaderboard: [Needs More Information]
Point of Contact: Gabriele Fanelli

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.

View C++ Code

/*
 * 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;
    }

}

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

@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 for adding this dataset.

Datasets:
biwi_kinect_head_pose

Dataset Card for Biwi Kinect Head Pose Database

Table of Contents

Dataset Description

Dataset Summary

Data Processing

Supported Tasks and Leaderboards

Languages

Dataset Structure

Data Instances

Data Fields

Data Splits

Dataset Creation

Curation Rationale

Source Data

Initial Data Collection and Normalization

Who are the source language producers?

Annotations

Annotation process

Who are the annotators?

Personal and Sensitive Information

Considerations for Using the Data

Social Impact of Dataset

Discussion of Biases

Other Known Limitations

Additional Information

Dataset Curators

Licensing Information

Citation Information

Contributions