MorphCast Emotion AI – FAQ

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Last Update April 1, 2024

What is MorphCast Emotion AI?

MorphCast Emotion AI is a technology that enables the recognition and analysis of facial emotions (and not only) through artificial intelligence. It is a state-of-the-art technology that uses machine learning algorithms to analyze facial expressions and detect emotions in real-time. MorphCast Emotion AI is designed to be integrated into web applications, making it accessible to a wide range of users, including businesses and researchers. By analyzing and interpreting emotional data, MorphCast Emotion AI can provide valuable insights into customer behavior, market trends, and more. It is a powerful tool that can be used to improve customer engagement, optimize marketing campaigns, and enhance the overall user experience.

What MorphCast Emotion AI is able to detect (how does it recognize emotions)?

For detailed information about what MorphCast Emotion AI is able to detect, please see this documentation about How our Emotion AI works.

How are the extracted data represented, and is there a possibility to download them in some standard format?

The extracted data from our Emotion AI are meticulously structured to ensure ease of understanding and analysis. Users have the flexibility to download this data in widely recognized formats, including CSV and JSON, catering to diverse analytical needs. Additionally, our platform offers a comprehensive Dashboard, equipped with charts and graphs, for a visual representation of the emotional analysis. This multifaceted approach allows for an in-depth exploration of the detected emotional states, facilitating a seamless integration into your analytical frameworks. A complete documentation about interpreting data generated by our Emotion AI, you can consult this guide offering a clear, in-depth explanation of all the charts and analytical tools used in the MorphCast products.

What are the benefits of using MorphCast Emotion AI client-side processing technology?

MorphCast Emotion AI’s client-side processing technology offers privacy, real-time response, scalability, cost-effectiveness, and a low carbon footprint. For detailed benefits, visit: advantages of choosing our client-side Emotion AI.

What industries can use MorphCast Emotion AI?

The software can be used in several industries, including:
– Emotion analysis: MorphCast Emotion AI can be used to analyze and profile online audiences, collecting valuable data to enhance business strategies.
– eLearning experiences: The software can be used to create emotionally interactive lessons that adapt to individual learners’ pace and improve the effectiveness and fun of learning experiences.
– HR: MorphCast Emotion AI can be used to analyze candidates during recruiting phases, and to deliver adaptive training paths based on employees’ interactions, emotional response, and level of engagement to improve personnel’s soft skills and boost performance.
– Product innovation: MorphCast offers flexible and user-friendly tools for creating proof-of-concepts and innovative products, participating in calls, and finding funds to finance disruptive ideas.
– Digital advertising: The software can help to capture the attention of online users, improve audience engagement, and boost digital campaign results through personalized and impressive emotionally interactive experiences.

How is the software trained and what about bias?

Our neural networks have been trained using custom datasets with huge amounts of faces, ranging from all ethnicities, ages and genders. Although the dataset is not shared, we acknowledge that there may be a possibility of race, gender, and age bias in the analysis results. However, we emphasize that the influence is not significant, and the MorphCast Emotion AI has been tested on standard test benches by an independent research center, confirming its accuracy among different ages, genders, and ethnicities.
For detailed information about how is the software trained and what about bias, please see this documentation about Responsibility, Transparency and Clarity.
We can confirm that the accuracy of our AI has been validated through tests on a standard market testbed, BU-4DFE, which included representation from various ethnicities such as Asian, Black, Hispanic/Latino, African American, and White. This ensures that our system is reliable and accurate in analyzing facial expressions across a broad demographic spectrum.
Anyway we invite you to take the possibility of bias into account and minimize its effects depending on the purpose of the analysis. It is essential to note that mitigating bias in AI algorithms is an ongoing challenge, and MorphCast’s approach to acknowledging its existence and working to minimize its effects is a step in the right direction.

How accurate and powerful is MorphCast Emotion AI?

The accuracy of MorphCast Emotion AI depends on various factors such as the lighting conditions and camera quality. However, our client-side algorithms have an accuracy level that is at par with the competitors who use server-side algorithms (see this independent publication: Emotion recognition in humans and machines using posed and spontaneous facial expression). The software is empowered by AI algorithms with minimal computation and size overhead, ensuring efficiency in resource utilization. Additionally, the large number of configurable parameters guarantees flexibility, while the default configuration has filters already tuned for common usages, making it ready-to-use. The intuitive interface makes it easy-to-use, and it is compatible with almost every modern browser. MorphCast Emotion AI has a modular architecture that ensures its scalability. It is capable of reaching even 20-30 analyses per second on PC devices and usually reaches seven analyses per second on most last-generation mobiles. The dynamic power-save optimizer is designed to optimize CPU and GPU load when available, making it a power-efficient solution.

Could you specify the optimal lighting conditions, particularly brightness levels, required for accurate face emotion analysis?

Lighting Requirements: 300 to 500 lux is often recommended for comfortable visibility and clear recording indoors and 750 to 1,000 lux for outdoor environment. 

What is the recommended distance between the camera and the subject for optimal emotion detection?

For optimal emotion detection, the recommended distance between the camera and the subject is typically a close-up range of about 30 to 60 cm (approximately 1 to 2 feet). This distance allows the software to capture facial expressions clearly. To aid in positioning, you can use an on-screen template to help users align their faces correctly. The size of the face template will adjust based on the distance, ensuring optimal positioning for accurate emotion analysis.

How should I position the camera for optimal performance when using this system?

Ensure that the camera is positioned at nose height of the viewer and that the face is directed straight towards it.

What lighting conditions should I avoid when setting up the camera for this system?

In addition to brightness, ensure there are no direct light sources behind the viewer or strong lateral sources that could create shadows on the face.

Are there any items or accessories that users should avoid wearing when using this system to ensure accurate facial expression analysis?

Make sure users do not have obstructing elements, such as sunglasses, covering the face, as they can affect the accuracy of facial expression analysis.

How can I configure the SDK for a higher input resolution to the Face Detector if my camera supports it, and what are the benefits of doing so?

If your camera supports it, you can configure the SDK with a higher input resolution to the Face Detector, allowing for the detection of faces even at distances greater than the indicated range.

Is there an option to adjust parameters to accommodate different distances from the camera, such as for outdoor advertising (OOH) applications?

Yes, the parameter ‘maxInputFrameSize’ in our SDK can be adjusted to accommodate different distances for facial analysis, such as for outdoor advertising (OOH) use. This parameter indirectly influences how far the face being analyzed can be from the camera. For detailed guidance on how to adjust this and other parameters, please refer to the technical documentation related to our SDK.

How would I measure and test confidence? Is it the amount of time spent being confident? or is there a way of identifying the depth of degrees?

For measuring confidence, consider using the “quadrant” outputs from our MorphCast Emotion AI SDK, specifically the “Conductive” quadrant. This approach, broader than identifying a specific mood like “Confident,” aligns well with confidence-related states and is grounded in appraisal theory. It offers a more encompassing view of emotional states akin to confidence.

If I have multiple faces in the same frame, is there a way to distinguish them in the output or generate multiple graphs depending on the number of faces?

Due to ethical considerations, which we at Morphcast hold in high regard, our artificial intelligence engine, MorphCast, has been deliberately designed to not recognize faces and to not track the behavior of the same face across the sequence of frames in a video stream or camera feed. Originally, it was designed to track, in each frame, the largest face if there are multiple faces present. The subsequent frame does not retain any identity information from the previous frame. Consequently, if two faces in successive frames alternate in size relative to each other, the engine will track each one alternately, unaware that the faces belong to two different individuals.

What is the Adjustable Angle Parameter and how does it relate to the Positivity Index in the context of emotional analysis using the SDK?

The Attention Index is a dynamic measure that evaluates a user’s level of focus or engagement with the screen. It takes into account whether the user’s face is within the webcam’s field of view, head position, and other indicators of emotional and mood behavior. This index is continually calculated, providing real-time insights into the attention levels of users. Importantly, the Attention Index is scaled from 0 to 1, where 0 indicates minimal or no attention and 1 signifies maximum attention.
Positivity Index
The Positivity Index is derived from the Arousal and Valence dimensions, part of the 2D emotional space model. Arousal indicates the level of engagement, and Valence represents the emotional positivity or negativity. The Positivity Index is also scaled from 0 to 1, where 0 represents a completely negative emotional state and 1 represents a completely positive state. 
Adjustable Angle Parameter: In the context of the Positivity Index, we have an adjustable angle parameter. This parameter is key in interpreting the emotional state within the 2D space of Arousal and Valence. It helps project the emotional state onto a single dimension, simplifying the complex emotional state into a single positivity score. By adjusting this angle, you can customize how different emotional states are interpreted and represented as a single value.
Practical Application: This means that depending on the angle you set, the SDK interprets and combines the arousal and valence values differently. This feature allows you to tailor the Positivity Index to better suit the specific needs or context of your application, it offers a means to calibrate how various emotional states are quantified and understood, providing a nuanced approach to emotional analysis.

Is MorphCast’s technology legally recognized for validating facial expressions?

Currently, there is no specific legal recognition for artificial intelligence (AI) technologies pertaining to facial expression analysis. The legislation regarding AI is evolving and continues to develop. The European Parliament recently passed the “AI Act”, a pioneering law in the field of AI. Preliminary information suggests that AI for emotion detection is classified in a category that requires special attention. Therefore, European companies, or those intending to operate in Europe, will need to fulfill certain obligations, such as providing detailed data on the training of their models to a specific European authority.
Once the final text of the law is available and the regulatory body is established, MorphCast will commit to following the required procedures to ensure compliance with the new regulations. This step demonstrates our commitment to legality and ethics in the use of artificial intelligence.

Are there documented cases where MorphCast data has been used as legal evidence?

Currently, there are no documented cases where MorphCast data has been used as legal evidence. This is in line with the current state of AI legislation, which has yet to define specific rules for the legal use of such technologies in judicial contexts.

Does MorphCast share the specific alghoritms and data sources used to train the AI?

Our training algorithms and specific data sources are currently subject to industrial secrecy.
The decision to keep these aspects confidential is driven by our duty to safeguard the substantial investments that have enabled the creation of our advanced AI technology. This approach is essential for maintaining competitive advantage and ensuring the ongoing viability and innovation of our products.
We understand the importance of transparency in the AI industry and are committed to upholding ethical standards and regulatory compliance. If in the future we decide to make our algorithms and data sources open source, we will do so in a manner that is public and transparent, while still respecting the interests of our stakeholders and the integrity of our intellectual assets.
We appreciate the interest in our methodologies and remain dedicated to advancing the field of AI in a responsible and sustainable manner, balancing the need for openness with the imperative to protect our investments and innovations.

What details can you provide about the dataset used for training MorphCast’s AI?

In line with our policy on confidentiality and the protection of our intellectual assets, we do not disclose specific details about the composition and size of the dataset used for training MorphCast’s AI. Similar to how the exclusive recipes of renowned AI (and not only AI) products, remain secret, we maintain the confidentiality of specific aspects of our training process to protect our investments and competitive edge.
However, we can confirm that the accuracy of our AI has been validated through tests on a standard market testbed, BU-4DFE, which included representation from various ethnicities such as Asian, Black, Hispanic/Latino, African American, and White. This ensures that our system is reliable and accurate in analyzing facial expressions across a broad demographic spectrum.
For those who wish to conduct more specific and detailed analyses, we are willing to provide the necessary tools for them to personally test the efficacy of our SDK on a testbed of their choice. We strongly believe in the capability of our system to meet the most demanding requirements and are open to collaborations that allow our clients to personally verify its effectiveness and accuracy.

What is the MorphCast’s Origin and background?

MorphCast is a registered trademark of Cynny S.p.A., an innovative Italian SME founded in 2013 in Florence by Stefano Bargagni, a serial internet entrepreneur with a background in computer science. Since 2014, the company has focused on researching and developing deep neural network algorithms for facial expression detection, receiving significant recognitions including four seals of excellence from the European Union’s Horizon2020 program and numerous mentions in Gartner research.
In terms of corporate social responsibility, MorphCast commits to operating with authenticity, transparency, integrity, and social responsibility. This includes a commitment to environmental protection, human rights, and personal data protection, as highlighted in their Code of Ethics and guidelines for the responsible use of Emotion AI.
Regarding transparency, all publicly available information about Cynny SpA can be found on our istitutional webpage. The page contains information on Cynny SpA’s corporate structure, including details about the board of directors and R&D team. It also provides insights into the company’s industrial and intellectual property rights. Additionally, there’s a comprehensive list of shareholders, resolutions from the general meeting of shareholders, foundational documents, chamber of commerce certificates, balance sheets, and more. For complete information, you can visit the webpage here. Please note that the content is in Italian; however, you are welcome to use any translation tool or AI-based language translator to fully understand the details.
MorphCast’s collaborations with research institutes like the CVC Center in Barcelona and the MICC in Florence, and partnerships with international entities in remote learning and coaching, demonstrate its commitment to promoting sustainable and socially responsible AI innovation.
MorphCast’s future vision envisages a transformative era where emotion AI becomes a cornerstone of human interactions and between humans and robots. The goal is to develop an ecosystem where humans, avatars, and robots coexist, benefiting from the emotional intelligence provided by MorphCast’s technology.

Does the MorphCast dataset include individuals from diverse ethnicities and backgrounds?

Yes, MorphCast’s Emotion AI technology, developed by Cynny S.p.A., utilizes a diverse dataset that includes images and videos from people of different ages, genders, and ethnicities. This broad representation is crucial for training the algorithms to accurately analyze facial expressions across various demographic groups. The technology emphasizes impartiality and does not process biometric data for the unique identification of individuals, ensuring privacy and ethical use. For more information see Responsibility, Transparency and Clarity.

Can MorphCast accurately analyze expressions across different demographic groups?

MorphCast’s Emotion AI technology is designed to estimate emotional states and apparent characteristics, such as age and gender, with varying degrees of probability and accuracy. The software, implemented as a JavaScript library, operates in the end user’s browser and does not store images or videos, ensuring data privacy. The accuracy of facial expression recognition can be influenced by factors like image quality, algorithm design, and the diversity of the training data. MorphCast’s algorithms, which employ deep learning techniques and are continuously improved through research, aim to minimize bias and provide reliable emotion recognition across different groups.

Does MorphCast’s technology rely on research from renowned experts like Paul Ekman?

Yes, MorphCast’s AI technology is informed by the research of leading experts in the field, including the work of Paul Ekman. The AI models used in MorphCast digitally reproduce the results from longstanding research and papers in the domain of emotion recognition and analysis. By grounding our technology in well-established scientific studies, we ensure a robust and credible foundation for our emotion AI systems.
MorphCast’s AI is trained using a variety of scholarly sources that contribute to its accuracy and reliability. Some of the key research works that have influenced our AI models include:
Russell, J., Lewicka, M. & Niit, T. (1989). A cross-cultural study of a circumplex model of affect. Journal of personality and social psychology, 57, 848–856.
Scherer, Klaus. (2005). Scherer KR. What are emotions? And how can they be measured? Soc Sci Inf 44: 695-729. Social Science Information. 44. 695-792. 
Ahn, Junghyun & Gobron, Stéphane & Silvestre, Quentin & Thalmann, Daniel. (2010). Asymmetrical Facial Expressions based on an Advanced Interpretation of Two-dimensional Russell Emotional Model. 
Paltoglou, G., & Thelwall, M. (2012). Seeing stars of valence and arousal in blog posts. IEEE Transactions on Affective Computing, 4(1), 116-123. 
Paul Ekman Basic-Emotions.

Are there any ethical concerns with using MorphCast Emotion AI?

As with any technology that involves the collection and processing of personal data, there are potential ethical concerns associated with using MorphCast Emotion AI. These concerns primarily revolve around issues related to privacy, fairness, and potential bias.
One major ethical concern is the potential misuse or mishandling of personal data, particularly emotional data, that may be collected through the use of Emotion AI. To address this concern, MorphCast Emotion AI has established a code of ethics and guidelines to ensure ethical and responsible behavior from all parties involved in the use of the technology. The guidelines emphasize the importance of obtaining explicit and informed consent from individuals before collecting or processing their emotional data, respecting the privacy and dignity of individuals, and being transparent about the capabilities and limitations of Emotion AI systems.
Another ethical concern is the potential for Emotion AI to perpetuate or exacerbate existing biases or discrimination. This could occur if the training data used to develop the algorithms for Emotion AI is biased or if the technology is used to make decisions that discriminate against certain groups of people. To address this concern, MorphCast Emotion AI has trained its neural networks using custom datasets with huge amounts of faces, ranging from all ethnicities, ages, and genders. Additionally, MorphCast Emotion AI advises its customers to take into account the existence of any bias case by case in order to cancel or minimize its effect as much as possible.
Finally, there is the concern that Emotion AI could be used to manipulate or exploit individuals. This could occur if the technology is used to intentionally or unintentionally manipulate an individual’s emotional state or to exploit their emotional vulnerabilities. To address this concern, MorphCast Emotion AI advocates for a responsible and ethical approach to the development and use of Emotion AI systems. Ethics and Guidelines for a Responsible Approach to Emotion AI emphasize the importance of designing and using Emotion AI systems in a way that respects the privacy and dignity of individuals and avoids using the technology in a way that discriminates against or unfairly disadvantages any particular group of individuals.
In summary, while there are potential ethical concerns associated with using MorphCast Emotion AI, the company has taken steps to address these concerns and promote a responsible and ethical approach to the development and use of the technology.

Are there any privacy concerns with using MorphCast Emotion AI?

Privacy is an important concern when it comes to using MorphCast Emotion AI, as it involves the processing of personal data, including collection of emotional data.
However, MorphCast Emotion AI takes privacy very seriously and has implemented measures to ensure that the privacy of users is protected. One key feature of MorphCast Emotion AI is that it works strictly on the client-side, meaning that the personal data from users (the camera frame with the user face) remains on their device and is not sent to any servers for analysis. This means that users have full control over their data and are not at risk of their data being accessed by third parties.
MorphCast Emotion AI also emphasizes the importance of obtaining explicit and informed consent from individuals before collecting or processing their data. This means that users must be fully informed about the purpose of the Emotion AI, how their data will be used, and any potential risks or benefits associated with participating. They must also have the opportunity to opt-in or opt-out of the data collection or processing.
In addition, MorphCast Emotion AI securely handles personal data in accordance with relevant laws and regulations. The company is fully GDPR compliant, which means that we adhere to strict data protection standards and ensure that users’ personal data is processed fairly and lawfully.
Overall, while privacy is an important concern with any technology that collects personal data, MorphCast Emotion AI takes measures to protect the privacy of users and ensure that their data is collected and processed in a responsible and ethical manner. More details on this topic you can finde here: privacy is an advantage. Please make sure to review the Privacy FAQ as well.

Can the software be integrated with other systems?

Yes, MorphCast Emotion AI can be integrated with other systems. MorphCast Emotion AI offers a large number of configurable parameters, which allows users to tailor the software to their specific needs. The integration of MorphCast Emotion AI with other systems can enhance the capabilities of those systems, enabling them to detect and analyze human emotions, and provide a more personalized and engaging experience for the end-users.

Which products/services does MorphCast offer?

MorphCast offers a wide range of products as a service, including video and photo analysis, integrations with chatGPT, avatars, video conferencing, and more. The company has also recently launched a web apps place featuring an increasing number of ready-to-use Emotion AI web applications.
Stay updated on all the services and products of MorphCast Emotion AI by consulting the menu item “Products” in our site.
The company also provides professional services such as consulting, training, and support for products and services.

What is the cost of using MorphCast Emotion AI?

MorphCast is known for being the most cost-effective facial Emotion AI service on the market.
Since we have no cloud AI computing costs to bear, we can offer our service at a price up to a thousand times lower than that of our competitors, meanwhile reducing the carbon footprint of our products.
We offer a dynamic pricing model that revolves around the usage time of license keys on a monthly basis. You start with a significant quota of free usage each month. If your usage surpasses this free limit, you’ll automatically move up to a higher tiered plan. Conversely, if your usage decreases in the following month, the plan will automatically adjust to a lower tier, reflecting your reduced usage.
On the MorphCast site we provide complete Plans and pricing.

Is it possible to obtain a license for free, non-commercial use?

Yes, if you are affiliated with a university or are conducting research, you may be eligible to obtain a no-cost license for non-commercial use. Startups may also receive special consideration for such licenses. Please proceed to acquire the necessary license through our web site channel, and then send us an email ( to inform us of your status. This will allow us to verify that you qualify for a no-cost, non-commercial license.

Consult also these additional FAQs:

  1. Emotion AI & Facial Emotion Recognition (FER)
  2. MorphCast Emotion AI (this document)
  3. Emotion AI Interactive Media Platform
  4. Emotion AI Media Player
  5. Emotion AI HTML5 SDK
  6. Emotion AI Web Apps
  7. MorphCast for ChatGPT
  8. MorphCast AI For ZOOM
  9. MorphCast Video Conference
  10. MorphCast for Privacy
  11. Cookie free domain