> ## Documentation Index
> Fetch the complete documentation index at: https://aegean.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# How Cameras Form Images

> Camera sensor models for robotics, from the pinhole model and real lenses to the full intrinsic and extrinsic calibration of a camera.

A camera turns light from a 3D scene into a 2D array of pixel values. To recover geometry from those pixels, you need a model of that mapping, and no real camera matches the simplest model exactly. The sections in this chapter build the model in three steps.

<CardGroup cols={2}>
  <Card title="Pinhole Camera Model" icon="camera" href="/aiml-common/lectures/sensor-models/cameras/pinhole-model">
    The pinhole projection, the intrinsic matrix, the lens distortion model, and coordinate conventions in ROS 2.
  </Card>

  <Card title="How Lenses Form Images" icon="eye" href="/aiml-common/lectures/sensor-models/cameras/lenses/index">
    Snell's law, the lensmaker formula, conjugate points, depth of field, concave lenses, and the Galilean telescope.
  </Card>

  <Card title="From World Points to Pixels" icon="cube" href="/aiml-common/lectures/sensor-models/cameras/camera-modeling/index">
    The full camera model with intrinsic and extrinsic parameters, backprojection, the horizon, and calibration from known points and from planar targets.
  </Card>
</CardGroup>

How the resulting images are represented and processed, from pixel arrays to filtering, is the subject of the [Image Processing](/aiml-common/lectures/image-processing/index) chapter.

***

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