> For the complete documentation index, see [llms.txt](https://docs-en.kivicube.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs-en.kivicube.com/ar-asset-creation-guide/image-marker/cloud-recognition-image.md).

# Cloud Recognition Image

Cloud Recognition Image: An image used for cloud-based image recognition.

Usage Scenario:

* **AR Scenes:** Cloud Recognition / Gyroscope
* **Collections:** Cloud Recognition / Gyroscope, Image AR&#x20;

<table data-header-hidden><thead><tr><th width="198.3758544921875"></th><th></th></tr></thead><tbody><tr><td>Type</td><td><strong>Description and Illustration</strong></td></tr><tr><td><strong>Valide Image Format</strong></td><td><ul><li>jpg</li><li>jpeg</li></ul></td></tr><tr><td><strong>Valid Color Mode</strong></td><td><p>Set the image to RGB to help detect any color deviation promptly.</p><div><figure><img src="/files/VVrGNxyJsZ5ddc2pZsLa" alt=""><figcaption></figcaption></figure></div><p><br>When exporting, check “Color Space → Convert to sRGB”, and verify after export to ensure no color deviation is present.</p><div><figure><img src="/files/sIDXemtnwKgI8PDr9utH" alt=""><figcaption></figcaption></figure></div><p></p><p></p></td></tr><tr><td><strong>Recommend Image Resolution</strong></td><td>The image resolution is recommended to be between 480×480 and 1280×1280, with around 800 being ideal.<img src="/files/9McbibWfZxW5lrJnMsL5" alt=""></td></tr><tr><td><strong>Recommend Image Aspect Ratio</strong></td><td><p>Landscape: 1:1 to 16:9 (Aspect Ratio 1 to 1.78)</p><p>Portrait: 9:16 to 1:1 (Aspect Ratio 0.56 to 1)<br><img src="/files/YRf8i7UhTMJSXfwn3AnY" alt=""><img src="/files/di6VG1ux8Nou7U5JXUZl" alt=""><img src="/files/TlVlxBbEfZ0GpsUAidk2" alt=""></p></td></tr><tr><td><strong>Rich Detail</strong></td><td><ul><li>The following are examples of poor-quality images:</li></ul><div><figure><img src="/files/9Y6oHVvuuipVrZegYFQ2" alt=""><figcaption></figcaption></figure><figure><img src="/files/Ubrdi0xxg9M1lEHJB4yX" alt=""><figcaption></figcaption></figure><figure><img src="/files/CItDr6CRdqFmnNc28WYS" alt=""><figcaption></figcaption></figure><figure><img src="/files/2MRySBMHh9ZTVEO9evw4" alt="" width="375"><figcaption></figcaption></figure></div><ul><li>For the cases above, you may use AI Recognition instead of Cloud Recognition.</li></ul></td></tr><tr><td><strong>Avoid extensive whitespace</strong></td><td><p>Minimize blank regions and ensure the main subject is clearly emphasized.</p><div><figure><img src="/files/SW0ChIbL8RyDSulJpSfr" alt=""><figcaption></figcaption></figure></div></td></tr><tr><td><strong>Basic Principles of Cloud Recognition</strong></td><td><ul><li>The image should contain sharp, well-defined details:</li></ul><p>A square typically contains around 4 feature points, while a circle contains almost none.</p><div><figure><img src="/files/JU3zpX1y8NK0Z8zv56Ol" alt="" width="129"><figcaption></figcaption></figure></div><div><figure><img src="/files/gT3gRbVaqVWhQ1aEhSPr" alt=""><figcaption></figcaption></figure></div><p><br></p><p>Therefore, avoid large circular shapes in the design whenever possible.</p><ul><li>Avoid soft, smooth edges and images with large gradient areas.</li></ul><div><figure><img src="/files/oiOgeMXG4uo1MitQF070" alt=""><figcaption></figcaption></figure></div></td></tr><tr><td><strong>Enhance Contrast</strong></td><td><p>Increasing the image contrast can significantly improve recognition accuracy. <br>Original: <img src="/files/ovNMoxqej4pojh4185z6" alt="Original"><br></p><p>Contrast Enhanced: <img src="/files/vxtZGupN3mCYHwE2yL1I" alt="Contrast Enhanced"></p><p>Recognition:</p><div><figure><img src="/files/PmzDvjBzRO6qXR4LUkeM" alt=""><figcaption></figcaption></figure></div><div><figure><img src="/files/lpbcif8m0duEsOxbsDqc" alt=""><figcaption></figcaption></figure></div><ul><li>More contrast examples:</li></ul><div><figure><img src="/files/36DGPwL0qDsF4an1yB0q" alt=""><figcaption></figcaption></figure></div></td></tr><tr><td><strong>Avoid Repetitive Pattern</strong></td><td><ul><li>The following repetitive images can technically be recognized, but they carry a higher risk of misrecognition<br>(If each repeated object contains rich detail, recognition may still be possible):</li></ul><div><figure><img src="/files/dTkYeL4Vv0N9HIMTtDZN" alt="" width="375"><figcaption></figcaption></figure><figure><img src="/files/X5jNgvWzdcFIF3Zddgge" alt="" width="375"><figcaption></figcaption></figure><figure><img src="/files/MoO9ezycKblmJwYGMtPV" alt="" width="375"><figcaption></figcaption></figure><figure><img src="/files/HIiXq9ak18F7zhUvULv7" alt="" width="344"><figcaption></figcaption></figure></div><ul><li>The following images, which are repetitive, symmetrical, and overly simple, cannot be recognized<br>(Symmetry reduces recognizability, and the lines are too uniform):</li></ul><div><figure><img src="/files/HwlBWdIOFLfDjBwzPpqg" alt="" width="353"><figcaption></figcaption></figure><figure><img src="/files/W667xYaqGwlQvGc0crwv" alt="" width="346"><figcaption></figcaption></figure><figure><img src="/files/x9gcmPGNVHl8DOCva00V" alt="" width="300"><figcaption></figcaption></figure><figure><img src="/files/BuRpY4MxGrzJtC8lF7CB" alt="" width="375"><figcaption></figcaption></figure><figure><img src="/files/9CJzOndpCyKy2nS34bPz" alt="" width="313"><figcaption></figcaption></figure></div><p><br></p></td></tr><tr><td><strong>Avoid Image Blur</strong></td><td><p>Avoid large areas of blur in the design whenever possible</p><p>Original: </p><div><figure><img src="/files/4SO2HJ0ZuDnR3AyQTeoi" alt=""><figcaption></figcaption></figure></div><p>Large Area of Blur:<br></p><div><figure><img src="/files/v2WdpDRTNZaBwf1YBWa5" alt=""><figcaption></figcaption></figure></div><p>Recognition:<br><img src="/files/RdJTvW0iMgly8wuCBN55" alt=""><img src="/files/cxIkKuLm2vyYVZpolJU4" alt=""></p></td></tr><tr><td><strong>Uniform Distribution of Feature Points</strong></td><td><ul><li>The image should have a uniform distribution of features.</li></ul><div><figure><img src="/files/jmG1R5WQXH0TGgtbf2XA" alt=""><figcaption></figcaption></figure></div><p></p><ul><li>As shown above, when only the lower-right corner contains dense details, it should be avoided.</li><li><p>The following example shows feature points concentrated in the lower-left corner - this should also be avoided:</p><p></p></li></ul><div><figure><img src="/files/v5hLIIN6IEXjjxMsZIGq" alt=""><figcaption></figcaption></figure></div></td></tr></tbody></table>
