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by Sharlin
460 days ago
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Nowadays they use pre-trained pattern recognition AI models, yes, which has become much more impressive (and CPU-intensive) with mirrorless cameras where the entire resolution of the main image sensor is available for analyzing the scene. Some higher-end traditional DSLRs have a "high"-resolution (around 0.1 MPix or so) metering sensor that is used to assist the AF system (eg. what Canon calls iSA and iTR [1]). Traditionally, cameras would just focus using the single focus point the photographer has selected, or if they have selected a larger area focusing mode, the camera would typically pick the closest point of a group of points, assuming that that's usually what the photographer is interested in. (Remember that traditional (D)SLRs have a discrete AF sensor with at most a few dozen focusing points to choose from!) In tracking AF modes (eg. Canon's Servo AF), depending on settings, the camera tries to avoid sudden shifts in focus even if a foreground object momentarily occludes the original target. Tracking AF also has to predict the subject's motion to prevent the focus from lagging behind a fast-moving subject. Higher-end cameras allow configuring the AF behavior in terms of how reactive vs "sticky" it should be when tracking a subject, and how linear the subject's motion is expected to be. [1] https://www.canon.com.hk/cpx/en/technical/pa_Overview_of_65-... |
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[1] https://cam.start.canon/en/C017/manual/html/UG-04_AF-Drive_0... [2] https://cam.start.canon/en/C017/manual/html/UG-04_AF-Drive_0... [3] https://cam.start.canon/en/C017/manual/html/UG-04_AF-Drive_0...