Develop a system that uses cameras and can admit authorized persons in a high security zone while sounding the alarm for others. Integral to this system is an embedding module that produces a ranking of similar faces (embedding vectors) to a face I will call anchor. In the figure above the anchor is the passport photo of the US President Barack Obama (x𝑎 ) as shown in the first CNN branch of the ranking module that produces 𝑓(x𝑎 ) at its output. The second branch (called positive) includes another CNN that is trained with other images of Barack Obama (x𝑝 ) while the third branch (called negative) is trained with other than Barack Obama's images (x𝑛). - I will get a 2048 vector 𝑓(x𝑎 ) out of the CNN that is assumed to be ResNet. - Triplet Loss is defined below: QUESTION: Using all of the ABOVE information about the system, draw a block diagram of the system that can be deployed in the field giving as output the desired ranking. Please include detailed descriptions in your block diagram drawing!
Question
Develop a system that uses cameras and can admit authorized persons in a high security zone while sounding the alarm for others. Integral to this system is an embedding module that produces a ranking of similar faces (embedding vectors) to a face I will call anchor. In the figure above the anchor is the passport photo of the US President Barack Obama (x𝑎 ) as shown in the first CNN branch of the ranking module that produces 𝑓(x𝑎 ) at its output. The second branch (called positive) includes another CNN that is trained with other images of Barack Obama (x𝑝 ) while the third branch (called negative) is trained with other than Barack Obama's images (x𝑛). - I will get a 2048 vector 𝑓(x𝑎 ) out of the CNN that is assumed to be ResNet. - Triplet Loss is defined below: QUESTION: Using all of the ABOVE information about the system, draw a block diagram of the system that can be deployed in the field giving as output the desired ranking. Please include detailed descriptions in your block diagram drawing!
Solution
As an AI, I'm unable to draw diagrams. However, I can guide you on how to create a block diagram for the system described. Here's a step-by-step guide:
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Input: Start with three inputs representing the anchor image (x𝑎), the positive image (x𝑝), and the negative image (x𝑛). These are the images that will be fed into the system.
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Convolutional Neural Networks (CNNs): Draw three parallel blocks, each representing a CNN. The anchor image is fed into the first CNN, the positive image into the second CNN, and the negative image into the third CNN. Label these blocks as "CNN for Anchor", "CNN for Positive", and "CNN for Negative" respectively.
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Embedding Vectors: Each CNN outputs an embedding vector. Draw an arrow from each CNN block to a new block representing the embedding vector it produces. Label these blocks as "Embedding Vector for Anchor (f(x𝑎))", "Embedding Vector for Positive (f(x𝑝))", and "Embedding Vector for Negative (f(x𝑛))" respectively.
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Triplet Loss: Draw a block representing the Triplet Loss function. Connect the embedding vector blocks to this block with arrows. The Triplet Loss function takes the three embedding vectors as input and calculates the loss.
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Ranking Module: Draw a block representing the Ranking Module. Connect the Triplet Loss block to this block with an arrow. The Ranking Module takes the loss as input and produces a ranking of similar faces.
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Output: Finally, draw an arrow from the Ranking Module block to a block representing the output. This is the final ranking of similar faces.
Remember to label all blocks and arrows clearly. The blocks represent different components of the system, and the arrows represent the flow of data between these components.
Similar Questions
将下列片段总结Counterarguments suggest that facial recognition technology has the potential to significantly enhance public safety and security by effectively identifying potential threats and criminals. Proponents of this viewpoint argue that the benefits derived from the implementation of surveillance systems that utilize facial recognition technology outweigh the potential privacy concerns that may arise. They contend that as long as appropriate safeguards and regulations are in place to prevent the misuse and abuse of this technology, its positive impact on society can be maximized.Proponents emphasize that facial recognition technology can play a crucial role in preventing and deterring criminal activities. By swiftly identifying individuals who pose a potential threat to public safety, law enforcement agencies can take proactive measures to mitigate risks and ensure the well-being of communities. This technology has the potential to enhance the efficiency and effectiveness of investigations, enabling law enforcement to identify and apprehend criminals more quickly, potentially preventing further harm.Moreover, proponents argue that the benefits of facial recognition technology extend beyond law enforcement. It can be utilized in various sectors, such as transportation, border control, and access control systems, to enhance security measures and streamline processes. For instance, airports can leverage facial recognition technology to expedite the identification and verification of passengers, reducing wait times and improving overall travel experiences. Similarly, businesses can utilize this technology to enhance security protocols, ensuring that only authorized individuals have access to restricted areas.While acknowledging the concerns surrounding privacy, proponents argue that appropriate safeguards and regulations can address these issues effectively. They emphasize the importance of implementing strict guidelines for data collection, storage, and access to ensure that facial recognition technology is used responsibly and ethically. This includes obtaining informed consent, anonymizing data whenever possible, and establishing clear protocols for data retention and deletion. By adhering to these safeguards, the potential for misuse and abuse of facial recognition technology can be minimized, while still reaping the benefits it offers in terms of public safety and security.In conclusion, proponents argue that facial recognition technology has the potential to significantly enhance public safety and security by effectively identifying potential threats and criminals. They contend that the benefits derived from the implementation of surveillance systems utilizing this technology outweigh the potential privacy concerns, as long as appropriate safeguards and regulations are in place to prevent misuse. By striking a balance between the benefits and concerns, society can harness the potential of facial recognition technology to create safer and more secure environments while respecting individual privacy rights.
Which of the following is not true about face detection?Low data storageImproved securityEasy to integrateAutomated identification
A user is able to unlock a door to a secure room via facial recognition. This is an example of __________ authentication.SSOmultifactorbiometricLDAP
Face recognition extends beyond detecting the presence of a human face to determine whose face it isTRUEFALSE
Face recognition system is based on _____________.
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