Knowledge Base

FaceReader 10 - Integration and Setup

Integration with The Observer XT

FaceReader data can be visualized and analyzed in The Observer XT, enabling integration with other observational and physiological data. The advanced video editing functions of The Observer XT can be used to create highlight clips.

If you have The Observer XT 13 (or newer) with the External Data Module and you observe live, you can use the Noldus network communication protocol N-Linx to control FaceReader with The Observer XT. When you start or stop the observation in The Observer XT, the FaceReader analysis will also start or stop. The FaceReader analysis and FaceReader video can automatically be imported into the observation. In addition it is possible to create a participant with camera analysis when creating an observation in The Observer XT.

Communication with Other Applications Using the FaceReader API

Facial expressions detected by FaceReader and other output values can be accessed real-time by other applications, making the program an ideal tool for research into affective computing and the design of adaptive interfaces. In other words, FaceReader allows other software programs to respond instantaneously to the emotional state of the user. The FaceReader API can send classification results to remote programs over TCP/IP. This API can be used in a .Net application to easily make a connection with FaceReader. For more information, refer to the Technical Note 'FaceReader 9 Application Programming Interface'.

Individual Calibration

This function enables the correction of person specific biases towards a certain emotional expression. A calibration model can be created using live camera input, or images or video of the test participant showing a neutral expression. If there is no calibration model selected, there is a possibility of using continuous calibration. In this mode, FaceReader continuously adapts to the bias of a certain user.

Set-Up

FaceReader achieves the best performance if it gets a good (video) image. Both the placement of the camera and the lighting of the subject's face are of crucial importance in obtaining reliable classification results.

Camera Position

The ideal position for the camera is directly in front of the subject's face. If the subject faces a computer screen, the camera can be placed either directly above or directly below the screen. Classification output might have a small bias towards the angry emotion when the camera is placed on top of the monitor and a small bias towards surprised when the camera is placed below the monitor. This is due to the fact that people tend to tilt their head when showing these emotions.

Illumination

The best results are achieved with diffuse frontal lighting. The light intensity or the color is less relevant. Strong reflections or shadows, for example caused by lights from the ceiling, should be avoided. Sideward lighting from a window will generally degrade performance. If the subject faces a computer screen, two columns of LED lights or two TL-tubes to either side of the monitor will give a good result under most circumstances.

In situations where interior lighting cannot be controlled, stronger lights (e.g. professional photo lamps) can be used to negate the effect of other undesirable light sources. Noldus provides illumination for the optimization of your set-up.

FaceReader contains a model quality bar, which gives you a good indication of how well the program is able to model the face depicted in the image.

Source: FaceReader 10 Technical Specifications, Noldus Information Technology