# Recognition Settings ## What are Recognition Settings? The **Recognition Settings** feature allows you to configure how the system **detects, groups, and recognizes faces** across your account. This is useful for tracking important faces, helping you manage the data, usage rights and [**consent**](/consent.md) that relate to the people that appear in your company's photos and videos more effectively. {% hint style="info" %} **Setting up " Settings" in HIVO will help:** *Using Recognition Settings, you can fine-tune the HIVO system to focus only on important faces, helping you manage your data efficiently and save time.* {% endhint %} ## How to use Recognition Settings * ⚠️ **User Right Required:** User must have the permission: **“Is Client Admin - User can manage the Client Profile”.** * Navigate to **Recognition Settings: Client Profile** → **Settings** → **Recognition Settings**
### 🔹 Step 1: Choose Main Option #### 👉 Option 1: Disable Recognition Vectors If this setting is **turned ON,** it means that the creation of vector data for new images uploaded to the Library will be disabled. * **Detection Still Works:** The system will still scan and identify faces in your images, and the bounding boxes (the frames around faces) will still be visible. * **Manual Assignment is Possible:** You can still manually select these detected appearances and assign them to a HIVO Recognition Profile.
#### How to completely Disable Recognition for the Account To effectively shut down vector-based recognition for your entire account, you must complete two steps: * Enable the **"Disable Recognition Vectors" setting**: This stops the creation of recognition data for all future uploads. * Enable the “[**Remove Untagged Faces**](https://support.hivo.co/client-profile/client-profile-settings/asset-and-metadata-management/recognition-settings#step-3-additional-actions-remove-untagged-faces)” action: This will wipe any existing vector data from past images that haven't been tagged yet. After these two steps, your account will no longer have any vector data available to perform automated face comparisons. #### 👉 Option 2: Only Track Known Faces * When this option is enabled: * Detected faces will **only be assigned to known people** on the **Recognition** page. * Unknown faces will: **Not** be grouped into **Anonymous** profiles and **Not** have **Vector Data** stored * **When to use:** * When you only need to track **known individuals** * When you want to **enhance privacy** and avoid storing unnecessary face data
#### 👉 Option 3: Manual Confirmation Required for Known Faces When this setting is turned ON, people detected in assets won’t be automatically assigned to existing profiles when a match is found. * Instead, a suggested match is made for the detection, which may be optionally confirmed or ignored. * The suggested matches can be found on the [**Approvals - Recognition page**](https://support.hivo.co/approvals/recognition-approval#how-to-manage-recognition-suggestion-approvals), or on the Assets themselves as inline suggestions. * A person in the Asset Library will not come up in searches until the suggested match is confirmed.
### 🔹 Step 2: Face Grouping & Detection Settings #### 1. Minimum Number of Faces to Group * Specify the **minimum number of similar faces** required to save the face as an **Anonymous person.** Once a face appears enough times, it will save as an **Anonymous person**, making it easier to identify the person later from the **Recognition page.** * **Default value:** * Leave blank to use the default value of **4** * Suitable for **small to medium** numbers of uploads * **Recommendations:** If uploading **a large number of images or faces**: * Increase the value to **10 or more** * Ensures only frequently appearing faces are saved as Anonymous profiles #### 2. Minimum Face Matching Size (%) Specify the **minimum size a face needs to be** in order to be detected. Very small faces may not be useful to keep track of. * **Default value:** Leave blank to use the default value of **0%** * **Recommendations: 2%** is useful for **ignoring very small faces** in crowd or wide-angle images #### 3. Minimum Face Confidence (%) Specify the **minimum confidence level** required for a face to be detected. * **Default value:** Leave blank to use the default value of **99%** * **Recommendations:** * **99% or higher** is recommended * Helps prevent **false positives**
#### 4. Minimum Face Similarity (%) Specify the **minimum similarity level** required for two faces to be matched as the **same person**. High similarity ensures that similar faces always belong to the same person. * **Default value:** Leave blank to use the default value of **97%** * **Recommendations:** * **97%** works well in most cases * **95%** may work better when uploading **a very small number of faces**, improving match rates ### 🔹 Step 3: Additional Actions - **Remove Untagged Faces** This tool is designed to purge legacy data, making it especially useful if the system captured anonymous faces **before "Only Track Known Faces" was enabled** or during periods when the setting was toggled.
* Users must explicitly check the box **"I Understand, Remove Untagged"** to confirm the action. * The system will delete all Vector data associated with untagged faces. Please note that this action is irreversible. **Additional Cleanup Options:** * **Remove Anonymous Faces:** Completely wipes anonymous face profiles from the Recognition page. * **Remove Bounding Boxes:** Eliminates face detection frames for unidentified individuals when viewing photos or videos. * If **UNCHECKED**: The system deletes the recognition data but still retain the bounding boxes on the image (acting as a placeholder for you to tag later). * If **CHECKED**: The system will wipe all traces. The bounding boxes surrounding all untagged faces will be completely removed from the Asset.
Then, save the changes so this takes effect for future Recognition. [You can read more about Recognition feature here. ](https://support.hivo.co/recognition) If you have any questions, don't hesitate to ask, we're always here to help! --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://support.hivo.co/client-profile/client-profile-settings/asset-and-metadata-management/recognition-settings.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.