> For the complete documentation index, see [llms.txt](https://linksprite.gitbook.io/deepcloud-face-recognition-illustration/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://linksprite.gitbook.io/deepcloud-face-recognition-illustration/deepcloud-face-recognition-illustration.md).

# DeepCloud:  Face Recognition Illustration

DeepCloud is the application platform of the Video Sense solution. Other tool in video sense incudes VMS, and AICraft, which is the tool used to generate AI models.&#x20;

The system diagram of the video sense solution is shown below:

<figure><img src="https://2231600349-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FVaZoy4xfaUtQRrCDrl94%2Fuploads%2FzjQziHgt2Hlu2jDHpyGr%2FScreen%20Shot%202023-08-15%20at%2011.51.27%20AM.png?alt=media&amp;token=d47d0534-b3c4-4417-b22a-c411e9114b62" alt=""><figcaption><p>Video Sense Solution </p></figcaption></figure>

{% hint style="info" %}
Resources of other tools part of Video Sense Solution:

* [VMS](https://linksprite.gitbook.io/video-sense-open-video-management-software/)
* [DeepCloud](https://linksprite.gitbook.io/deepcloud-the-ai-application-platform/)&#x20;
* [AIBox](https://linksprite.gitbook.io/aibox-the-edge-box-that-runs-video-analytics/)
* [AICraft](https://linksprite.gitbook.io/aicraft-the-ai-application-generation-tool/)
* [TIYCam](https://linksprite.gitbook.io/build-applications-for-tiycam/)
  {% endhint %}

The AIBox container can be configured to run various of AI video analytics algorithms, such as human detection, face detection, vehicle detection and license plate detection, etc. In this article, we will go cover what deepcloud (the application platform) can offer when the AIbox container has face detection algorithm running.

## Problem&#x20;

<figure><img src="https://2231600349-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FVaZoy4xfaUtQRrCDrl94%2Fuploads%2FrNE4WkbvYqbm52QckXRi%2FPicture1.png?alt=media&amp;token=f767f972-9360-4914-92d8-6eb06183ef41" alt=""><figcaption><p>Shoplifter in Store</p></figcaption></figure>

When the staff of retail store suspects shoplifting, security needs to review the playback footage tens of hours.

<figure><img src="https://2231600349-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FVaZoy4xfaUtQRrCDrl94%2Fuploads%2FQfjtsRBe25SeHYp5n29Y%2FPicture1.png?alt=media&amp;token=a7245d52-b3ce-43d4-86ab-5121610176d8" alt=""><figcaption><p>Security spends tens of hours to look for events</p></figcaption></figure>

Shoplifting becomes a big cost for retail, and some store operators being to use shame wall to deter the potential shoplifter.&#x20;

<figure><img src="https://2231600349-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FVaZoy4xfaUtQRrCDrl94%2Fuploads%2FqktIk5ss095vcZvIluCe%2FPicture1.png?alt=media&amp;token=6a152de3-f503-4ec9-9b6a-154579673d68" alt=""><figcaption><p>Shame Wall</p></figcaption></figure>

By digitize these shame wall, deepcloud can share these shoplifers across the entire retail chains. If one shoplifter steals in one store, and verified by the security, their faces can be stored and later the system can send the alert across the chain (user can define if he wants to share across all of his stores or just single store).

The alerts can be sent to the staff phone or dedicated terminal that resides near the checkout table or security.

<figure><img src="https://2231600349-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FVaZoy4xfaUtQRrCDrl94%2Fuploads%2FFLj7CFLj7YczFuN9cFuW%2FPicture1.png?alt=media&amp;token=1eefb2ee-9ee6-4eac-b5e2-0c0d145be3e0" alt=""><figcaption><p>Mobile APP alert</p></figcaption></figure>

<figure><img src="https://2231600349-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FVaZoy4xfaUtQRrCDrl94%2Fuploads%2F8CWOqRUBaNlZUB3nggvI%2FPicture1.jpg?alt=media&amp;token=b02fb8fd-9372-4641-9f3b-0a620bea95dc" alt=""><figcaption><p>Dedicated alert terminal </p></figcaption></figure>

## Web Portal&#x20;

Deepcloud web portal offers a convient way to check the faces and video footage.

<figure><img src="https://2231600349-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FVaZoy4xfaUtQRrCDrl94%2Fuploads%2FrSqrWo2Usd0LyqJS1dVL%2FPicture1.png?alt=media&amp;token=2d5a9c52-6d20-46a3-9a28-71c9d69342c3" alt=""><figcaption><p>Face Clustering </p></figcaption></figure>

When security identified a new theft, they can click the face to see all instances, and click “create a new subject” to add this face to the database. Again, this newly  contributed theft will be shared across all stores (if authorized). When working with Video Sense VMS, clicking on the face will show the video clip of that moment.&#x20;

## Mobile APP

<figure><img src="https://2231600349-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FVaZoy4xfaUtQRrCDrl94%2Fuploads%2FN6TCutGnK0QT4ZA4NLgx%2FScreen%20Shot%202023-08-15%20at%201.24.25%20PM.png?alt=media&amp;token=d019d5e1-f4d5-4de3-8a77-f96ec604f2d5" alt=""><figcaption><p>Face logo</p></figcaption></figure>

<figure><img src="https://2231600349-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FVaZoy4xfaUtQRrCDrl94%2Fuploads%2FaojVWHGd8HvcybPLxAbS%2FPicture1.png?alt=media&amp;token=1693ba4d-fb07-42bd-9f19-a15ad3ce92d3" alt=""><figcaption></figcaption></figure>

Alerts will be pushed to mobile device and will be displayed under visiting records.

<figure><img src="https://2231600349-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FVaZoy4xfaUtQRrCDrl94%2Fuploads%2FZUjpcXtDLCNju7CZG543%2FPicture1.png?alt=media&amp;token=36b7bcc8-8199-4994-af5c-7e7b80e8ddfe" alt=""><figcaption></figcaption></figure>

The cameras of all stores will be organized per store.

The face clustering works even during night:

<figure><img src="https://2231600349-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FVaZoy4xfaUtQRrCDrl94%2Fuploads%2FZrGQwJwur5cihR8uSyUa%2FPicture1.png?alt=media&amp;token=35af4657-c455-4181-b289-40e162f2636e" alt=""><figcaption><p>Face match between daytime and night time </p></figcaption></figure>
