Contact Points
Trade name: Facial Expression Analysis System, Product brand name: FaceReader; Manufacturer name: Noldus; Model: 9; Part number: FaceReader 9.
Salient Characteristics: FaceReader software is fast, flexible, objective, accurate, and easy to use. It immediately analyzes data (live, video, or still images), saving valuable time. The option to record audio as well as video makes it possible to hear what people have been saying – for example, during human-computer interactions, or while watching stimuli. FaceReader is the best automated system for the recognition of specific properties in facial images and expressions. Aside from the basic or universal facial expressions, it is possible to define Custom Expressions. Additionally, FaceReader can recognize a neutral state and analyze contempt. FaceReader adjusts the analysis to the model that best fits the research, adapting to variables such as age of participants. According to a validation study using the ADFES data set, FaceReader 9 delivered accurate performance for emotion classification that is comparable to human observers.
1) One software license key and software package
2) One 4-hour session of remote training
3) One three-year service contract
Road, Suite 203 Leesburg, VA 20176 Contact: Sarah Adams Phone: 703-771-0440
Email: sales@noldus.com
source, and competition is precluded for the reasons indicated below. There are no
substitutes available.
The essential characteristics of the FaceReader software that limit the availability to a
sole source is FaceReader is the most widely used Facial Recognition software in
academia today. This software will allow us to estimate the underlying emotional state of
our participants which is central to the research we do, as well as combine our data
collected by our collaborators, allowing for substantially more powerful studies.
Moreover, FaceReader can be integrated easily with the existing multimodal
psychophysiological equipment setup we currently have in our behavioral testing room in
Building 10 OP4 which would allow us to conduct multimodal research on decisionmaking
in mental disorders.
Only this suggested source can furnish the requirements described above to the
exclusion of other sources. Purchasing another software package would cause
irreparable harm to our ongoing experiments and research. Furthermore, the use of the
FaceReader software will allow cross-site aggregation of data and reduce variability.
As previously mentioned, UCDN is focusing on characterizing factors that affect decision-making in mental disorders such as mood disorders, substance use, and chronic pain. This research involves the study of emotional states during decision-making. In the last decade, the improvement of machine learning and AI methods for facial information processing has been substantial. As such, many top publications in psychology and cognitive neuroscience now require objective measures of emotional state in addition to self-report. Due to the nature of our experiments, portability and accuracy are two important factors that guide our choice of this system. We currently require a facial expression detection software for our behavioral testing rooms in Building 10, OP4. Other laboratories at NIH have acquired this software because of its superior quality and security compared to others available in the market. It is the most widely used Facial Emotion Recognition software in academia today. This will allow us to estimate the underlying emotional state of our participant which is central to the research we do, as well as combine our data with data collected by our collaborators, allowing for substantially more powerful studies. Moreover, FaceReader can be integrated easily with the existing multimodal psychophysiological equipment setup we currently have in our behavioral testing room in Building 10 OP4 which would allow us to conduct multi-modal research on decision-making in mental disorders.
Interested parties may identify in writing their interest and capability in response to this requirement. Responses to this notice shall contain sufficient information to establish the interested parties’ bona-fide capabilities for fulfilling the requirement and include: unit price, list price, shipping and handling costs, the delivery period after contract award, the prompt payment discount terms, the F.O.B. Point (Destination or Origin), the Dun & Bradstreet Number (DUNS), the Taxpayer Identification Number (TIN), and the certification of business size. All offerors must have an active registration in the System for Award Management (SAM) www.sam.gov.
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