WoodyFaceDetection

Additional

Language
Java
Version
1.1.0 (May 23, 2015)
Created
Aug 28, 2014
Updated
Oct 24, 2015 (Retired)
Owner
Paul Blundell (blundell)
Contributor
Paul Blundell (blundell)
1
Activity
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Source code
APK file

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Woody Face Detection

Is a library to simplify the detection of faces using the front facing camera.

Named after a pioneer of automated facial recognition Woody Bledsoe.

Adding to your project

The Demo App shows some simple use cases.

As an example a one liner for using in an Activity would be like this:

    @Override
    protected void onCreate(Bundle savedInstanceState) {
        super.onCreate(savedInstanceState);
        Woody.onCreateMonitor(this);
    }

Then you have callbacks like so:

    @Override
    public void onFaceDetected() {

    }

    @Override
    public void onFaceTimedOut() {

    }

    @Override
    public void onFaceDetectionNonRecoverableError() {

    }

Release change log

compile 'com.blundell:woody:1.1.1'

Further Reading

During 1964 and 1965, Bledsoe, along with Helen Chan and Charles Bisson, worked on using the computer to recognize human faces (Bledsoe 1966a, 1966b; Bledsoe and Chan 1965). He was proud of this work, but because the funding was provided by an unnamed intelligence agency that did not allow much publicity, little of the work was published. Given a large database of images (in effect, a book of mug shots) and a photograph, the problem was to select from the database a small set of records such that one of the image records matched the photograph. The success of the method could be measured in terms of the ratio of the answer list to the number of records in the database. Bledsoe (1966a) described the following difficulties:

" This recognition problem is made difficult by the great variability in head rotation and tilt, lighting intensity and angle, facial expression, aging, etc. Some other attempts at facial recognition by machine have allowed for little or no variability in these quantities. Yet the method of correlation (or pattern matching) of unprocessed optical data, which is often used by some researchers, is certain to fail in cases where the variability is great. In particular, the correlation is very low between two pictures of the same person with two different head rotations. "

License

(c) Copyright 2014 Paul Blundell

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

   http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.