Body: <p>I'm trying to use AI and computer vision techniques to identify scene changes for a camera. Something like this:</p>
  <p><a href="https://i.sstatic.net/0U2jE.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/0U2jE.png" alt="enter image description here" /></a></p>
  <p><a href="https://i.sstatic.net/2V8O3.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/2V8O3.png" alt="enter image description here" /></a></p>
  <p><strong>What are some approaches to do this? Any ideas?</strong></p>
  <p>The scene is static. Somewhere I saw a user trains the app with multiple images of normal scenes, and the app monitors the amount of pixel change from the trained images. And it issues an alarm when the amount of pixel change exceeds a threshold for a specified time period. But it should be more complex than that. A human may walk around or shadows and sunlight might affect the scene, so it won't be a scene change and no anomaly.</p>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2023-07-12T18:58:04.607Z
Comments.Text: If you have only such static scene and want to know if a static object where removed, you probably dont dont need deep learning. Just do background subtraction.
Comments.UserDisplayName: Lelouch
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2023-07-12T19:03:29.623Z
Comments.Text: It is static; but remember we have shades, shadows and humans passing. Does it work? Actually a simpler approach would be better!
Comments.UserDisplayName: Mary
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2023-09-15T11:10:16.730Z
Comments.Text: What they are suggesting is literally do a difference on the two images. The pixels will be different and you will know that something has changed.
Comments.UserDisplayName: Ted Taylor of Life
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2023-09-30T15:11:45.710Z
Comments.Text: crosspost: https://forum.opencv.org/t/door-blockage-detection-using-opencv/13927
Comments.UserDisplayName: Christoph Rackwitz
Tags: <neural-networks><deep-learning><computer-vision><object-detection><image-segmentation>
Title: Use AI/Computer Vision to detect scene changes
UserDisplayName: Mary
ThreadText: # Use AI/Computer Vision to detect scene changes
  
  (Asked by: username_0 on 2023-07-12)
  
  I'm trying to use AI and computer vision techniques to identify scene changes for a camera. Something like this:
  
  [![enter image description here](https://i.sstatic.net/0U2jE.png)](https://i.sstatic.net/0U2jE.png)
  
  [![enter image description here](https://i.sstatic.net/2V8O3.png)](https://i.sstatic.net/2V8O3.png)
  
  **What are some approaches to do this? Any ideas?**
  
  The scene is static. Somewhere I saw a user trains the app with multiple images of normal scenes, and the app monitors the amount of pixel change from the trained images. And it issues an alarm when the amount of pixel change exceeds a threshold for a specified time period. But it should be more complex than that. A human may walk around or shadows and sunlight might affect the scene, so it won't be a scene change and no anomaly.
  
  **Tags:** neural-networks, deep-learning, computer-vision, object-detection, image-segmentation
  > **Comments:**
  > **username_1**: If you have only such static scene and want to know if a static object where removed, you probably dont dont need deep learning. Just do background subtraction.  
  > **username_0**: It is static; but remember we have shades, shadows and humans passing. Does it work? Actually a simpler approach would be better!  
  > **username_2**: What they are suggesting is literally do a difference on the two images. The pixels will be different and you will know that something has changed.  
  > **username_3**: crosspost: https://forum.opencv.org/t/door-blockage-detection-using-opencv/13927  
  
  ---
  
  ## 0 answers
  
  