Affectiva, Inc.

Evan Kodra

Rana El Kaliouby

Richard Scott Sadowsky

Daniel Bender

Oliver Ernst Nowak

Panu James Turcot

Thibaud Senechal

Timothy Peacock

Gregory Poulin

Graham John Page

Andrew Edwin Dreisch

Melissa Sue Burke

Data on a user interacting with a media presentation is collected at a client device. The data includes facial image data of the user. The facial image data is analyzed to extract cognitive state content of the user. One or more emotional intensity metrics are generated. The metrics are based on the cognitive state content. The media presentation is manipulated, based on the emotional intensity metrics and the cognitive state content. An engagement score for the media presentation is provided. The engagement score is based on the emotional intensity metric. A facial expression metric and a cognitive state metric are generated for the user. The manipulating includes optimization of the previously viewed media presentation. The optimization changes various aspects of the media presentation, including the length of different portions of the media presentation, the overall length of the media presentation, character selection, music selection, advertisement placement, and brand reveal time.

Media manipulation using cognitive state metric analysis

An individual can exhibit one or more mental states when reacting to a stimulus. A camera or other monitoring device can be used to collect, on an intermittent basis, mental state data including facial data. The mental state data can be interpolated between the intermittent collecting. The facial data can be obtained from a series of images of the individual where the images are captured intermittently. A second face can be identified, and the first face and the second face can be tracked.

Sporadic collection with mobile affect data

Mental state data is gathered from a plurality of people and analyzed in order to determine mental state information. Metrics are generated based on the mental state information gathered as the people view media presentations. Norms, defined as the quantitative measures of the mental states of a plurality of people as they view the media presentation, are determined based on the mental state information metrics. The norms can be determined based on various viewer criteria including country of residence, demographic group, or device type on which the media presentation is viewed. Responses to new media are then compared against norms to determine the effectiveness of the new media presentations.

Mental state analysis for norm generation

A user interacts with various pieces of technology to perform numerous tasks and activities. Reactions can be observed and mental states inferred from these performances. Multiple devices, including mobile devices, can observe and record or transmit a user's mental state data. The mental state data collected from the multiple devices can be used to analyze the mental states of the user. The mental state data can be in the form of facial expressions, electrodermal activity, movements, or other detectable manifestations. Multiple cameras on the multiple devices can be usefully employed to collect facial data. An output can be rendered based on an analysis of the mental state data.

Collection of affect data from multiple mobile devices

A user may react to an interaction by exhibiting a mental state. A camera or other monitoring device can be used to capture one or more manifestations of the user's mental state, such as facial expressions, electrodermal activity, or movements. However, there may be conditions where the monitoring device is not able to detect the manifestation continually. Thus, various capabilities and implementations are described where the mental state data is collected on an intermittent basis, analyzed, and an output rendered based on the analysis of the mental state data.

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Waltham, MA, United States of America

Evan Kodra