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FDDB
2D Ellipse
Face
|...
License: Unknown

Overview

The Face Detection Data Set and Benchmark (FDDB) is a data set of face regions designed for
studying the problem of unconstrained face detection. This data set contains the annotations
for 5171 faces in a set of 2845 images taken from the
Faces in the Wild data set.

Data Annotation

Face Detection Data Set and Benchmark
University of Massachusetts - Amherst

Face annotations

Uncompressing the "FDDB-folds.tgz" file creates a directory "FDDB-folds", which contains files
with names: FDDB-fold-xx.txt and FDDB-fold-xx-ellipseList.txt, where xx = {01, 02, ..., 10}
represents the fold-index. Each line in the FDDB-fold-xx.txt file specifies a path to
an image in the above-mentioned data set. For instance, the entry 2002/07/19/big/img_130
corresponds to originalPics/2002/07/19/big/img_130.jpg.

The corresponding annotations are
included in the file "FDDB-fold-xx-ellipseList.txt" in the following format:

<image name i>
<number of faces in this image =im>
<face i1>
<face i2>
...
<face im>

Here, each face is denoted by: <major_axis_radius minor_axis_radius angle center_x center_y 1>.

Detection output

To be recognized by the evaluation code, the detection output is expected in the following format:

<image name i>
<number of faces in this image =im>
<face i1>
<face i2>
...
<face im>

where the representation
of a face depends on the specifics of the shape of the hypothesized image region. The evaluation
code supports the following shapes:

  • Rectangular regions
    Each face region is represented as:
    <left_x top_y width height detection_score>

  • Elliptical regions
    Each face region is represented as:
    <major_axis_radius minor_axis_radius angle center_x center_y detection_score>.

Also, the order of images in the output file is expected
to be the same as the order in the file annotatedList.txt.

Citation

Please cite as:
Vidit Jain and Erik Learned-Miller.
FDDB: A Benchmark for Face Detection in Unconstrained Settings.
Technical Report UM-CS-2010-009, Dept. of Computer Science, University of Massachusetts, Amherst. 2010.

BibTeX entry:

@TechReport{fddbTech,
  author = {Vidit Jain and Erik Learned-Miller},
  title =  {FDDB: A Benchmark for Face Detection in Unconstrained Settings},
  institution =  {University of Massachusetts, Amherst},
  year = {2010},
  number = {UM-CS-2010-009}
  }
Data Summary
Type
Image,
Amount
2.845K
Size
552.56MB
Provided by
Vision Lab
The Computer Vision Laboratory was established in the Computer Science Department at the University of Massachusetts in 1974 with the goal of investigating the scientific principles underlying the construction of integrated vision systems and the application of vision to problems of real-world importance. The emphasis of our work is on vision systems that are capable of functioning flexibly and robustly in complex changing environments.
| Amount 2.845K | Size 552.56MB
FDDB
2D Ellipse
Face
License: Unknown

Overview

The Face Detection Data Set and Benchmark (FDDB) is a data set of face regions designed for
studying the problem of unconstrained face detection. This data set contains the annotations
for 5171 faces in a set of 2845 images taken from the
Faces in the Wild data set.

Data Annotation

Face Detection Data Set and Benchmark
University of Massachusetts - Amherst

Face annotations

Uncompressing the "FDDB-folds.tgz" file creates a directory "FDDB-folds", which contains files
with names: FDDB-fold-xx.txt and FDDB-fold-xx-ellipseList.txt, where xx = {01, 02, ..., 10}
represents the fold-index. Each line in the FDDB-fold-xx.txt file specifies a path to
an image in the above-mentioned data set. For instance, the entry 2002/07/19/big/img_130
corresponds to originalPics/2002/07/19/big/img_130.jpg.

The corresponding annotations are
included in the file "FDDB-fold-xx-ellipseList.txt" in the following format:

<image name i>
<number of faces in this image =im>
<face i1>
<face i2>
...
<face im>

Here, each face is denoted by: <major_axis_radius minor_axis_radius angle center_x center_y 1>.

Detection output

To be recognized by the evaluation code, the detection output is expected in the following format:

<image name i>
<number of faces in this image =im>
<face i1>
<face i2>
...
<face im>

where the representation
of a face depends on the specifics of the shape of the hypothesized image region. The evaluation
code supports the following shapes:

  • Rectangular regions
    Each face region is represented as:
    <left_x top_y width height detection_score>

  • Elliptical regions
    Each face region is represented as:
    <major_axis_radius minor_axis_radius angle center_x center_y detection_score>.

Also, the order of images in the output file is expected
to be the same as the order in the file annotatedList.txt.

Citation

Please cite as:
Vidit Jain and Erik Learned-Miller.
FDDB: A Benchmark for Face Detection in Unconstrained Settings.
Technical Report UM-CS-2010-009, Dept. of Computer Science, University of Massachusetts, Amherst. 2010.

BibTeX entry:

@TechReport{fddbTech,
  author = {Vidit Jain and Erik Learned-Miller},
  title =  {FDDB: A Benchmark for Face Detection in Unconstrained Settings},
  institution =  {University of Massachusetts, Amherst},
  year = {2010},
  number = {UM-CS-2010-009}
  }
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