Datasets:

Task Categories: other
Languages: English
Multilinguality: monolingual
Size Categories: 10K<n<100K
Language Creators: expert-generated
Annotations Creators: expert-generated
Source Datasets: original
Licenses: other
Dataset Preview Go to dataset viewer
The dataset preview is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code:   StreamingRowsError
Exception:    NotImplementedError
Message:      Extraction protocol for TAR archives like 'https://data.vision.ee.ethz.ch/cvl/gfanelli/kinect_head_pose_db.tgz' is not implemented in streaming mode. Please use `dl_manager.iter_archive` instead.
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/responses/first_rows.py", line 337, in get_first_rows_response
                  rows = get_rows(dataset, config, split, streaming=True, rows_max_number=rows_max_number, hf_token=hf_token)
                File "/src/services/worker/src/worker/utils.py", line 123, in decorator
                  return func(*args, **kwargs)
                File "/src/services/worker/src/worker/responses/first_rows.py", line 65, in get_rows
                  ds = load_dataset(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1739, in load_dataset
                  return builder_instance.as_streaming_dataset(split=split)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1025, in as_streaming_dataset
                  splits_generators = {sg.name: sg for sg in self._split_generators(dl_manager)}
                File "/tmp/modules-cache/datasets_modules/datasets/biwi_kinect_head_pose/cfd0d6c65720e5980ccfa19311e60fa8525c7635347529c0ff09532530dd26d0/biwi_kinect_head_pose.py", line 124, in _split_generators
                  data_dir = dl_manager.download_and_extract(_URLS)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/download/streaming_download_manager.py", line 944, in download_and_extract
                  return self.extract(self.download(url_or_urls))
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/download/streaming_download_manager.py", line 907, in extract
                  urlpaths = map_nested(self._extract, path_or_paths, map_tuple=True)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/utils/py_utils.py", line 393, in map_nested
                  mapped = [
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/utils/py_utils.py", line 394, in <listcomp>
                  _single_map_nested((function, obj, types, None, True, None))
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/utils/py_utils.py", line 330, in _single_map_nested
                  return function(data_struct)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/download/streaming_download_manager.py", line 912, in _extract
                  protocol = _get_extraction_protocol(urlpath, use_auth_token=self.download_config.use_auth_token)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/download/streaming_download_manager.py", line 390, in _get_extraction_protocol
                  raise NotImplementedError(
              NotImplementedError: Extraction protocol for TAR archives like 'https://data.vision.ee.ethz.ch/cvl/gfanelli/kinect_head_pose_db.tgz' is not implemented in streaming mode. Please use `dl_manager.iter_archive` instead.

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Dataset Card for Biwi Kinect Head Pose Database

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.