When.com Web Search

Search results

  1. Results From The WOW.Com Content Network
  2. Artificial intelligence for video surveillance - Wikipedia

    en.wikipedia.org/wiki/Artificial_intelligence...

    Extensive video surveillance systems were relegated to merely recording for possible forensic use to identify someone, after the fact of a theft, arson, attack or incident. Where wide angle camera views were employed, particularly for large outdoor areas, severe limitations were discovered even for this purpose due to insufficient resolution. [4]

  3. Object detection - Wikipedia

    en.wikipedia.org/wiki/Object_detection

    Objects detected with OpenCV's Deep Neural Network module (dnn) by using a YOLOv3 model trained on COCO dataset capable to detect objects of 80 common classes. Object detection is a computer technology related to computer vision and image processing that deals with detecting instances of semantic objects of a certain class (such as humans, buildings, or cars) in digital images and videos. [1]

  4. Artificial intelligence content detection - Wikipedia

    en.wikipedia.org/wiki/Artificial_intelligence...

    Artificial intelligence detection software aims to determine whether some content (text, image, video or audio) was generated using artificial intelligence (AI). However, the reliability of such software is a topic of debate, [ 1 ] and there are concerns about the potential misapplication of AI detection software by educators.

  5. Video content analysis - Wikipedia

    en.wikipedia.org/wiki/Video_content_analysis

    Flame and smoke detection: IP cameras with intelligent video surveillance technology can be used to detect flame and smoke in 15–20 seconds or even less because of the built-in DSP chip. The chip processes algorithms that analyzes the videos captured for flame and smoke characteristics such as color chrominance, flickering ratio, shape ...

  6. Foreground detection - Wikipedia

    en.wikipedia.org/wiki/Foreground_detection

    This averaging refers to averaging corresponding pixels in the given images. N would depend on the video speed (number of images per second in the video) and the amount of movement in the video. [4] After calculating the background B(x,y,t) we can then subtract it from the image V(x,y,t) at time t = t and threshold it. Thus the foreground is:

  7. Smart camera - Wikipedia

    en.wikipedia.org/wiki/Smart_camera

    Early smart camera (ca. 1985, in red) with an 8MHz Z80 compared to a modern device featuring Texas Instruments' C64 @1GHz. A smart camera is a machine vision system which, in addition to image capture circuitry, is capable of extracting application-specific information from the captured images, along with generating event descriptions or making decisions that are used in an intelligent and ...

  8. Image sensor - Wikipedia

    en.wikipedia.org/wiki/Image_sensor

    A micrograph of the corner of the photosensor array of a webcam digital camera Image sensor (upper left) on the motherboard of a Nikon Coolpix L2 6 MP. The two main types of digital image sensors are the charge-coupled device (CCD) and the active-pixel sensor (CMOS sensor), fabricated in complementary MOS (CMOS) or N-type MOS (NMOS or Live MOS) technologies.

  9. Shot transition detection - Wikipedia

    en.wikipedia.org/wiki/Shot_transition_detection

    Shot transition detection (or simply shot detection) also called cut detection is a field of research of video processing. Its subject is the automated detection of transitions between shots in digital video with the purpose of temporal segmentation of videos.