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Time-of-flight camera

Time-of-flight camera is a computer science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Time-of-flight camera rather than just read about it. In short: A time-of-flight camera (ToF camera), also known as time-of-flight sensor (ToF sensor), is a range imaging camera system for measuring distances between the camera and the subject for each point of the image based on time-of-flight, the round trip time of an artificial light signal, as provided by a laser or an LED. Laser-based time-of-flight cameras are part of a broader class of scannerless LIDAR, in which the ent…

Time-of-flight camera — main illustration
Time-of-flight camera — illustration

Key takeaways

  • Time-of-flight camera belongs to computer science; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Time-of-flight camera to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Time-of-flight camera from memory before moving on to harder problems.

Reference excerpt

A time-of-flight camera (ToF camera), also known as time-of-flight sensor (ToF sensor), is a range imaging camera system for measuring distances between the camera and the subject for each point of the image based on time-of-flight, the round trip time of an artificial light signal, as provided by a laser or an LED. Laser-based time-of-flight cameras are part of a broader class of scannerless LIDAR, in which the entire scene is captured with each laser pulse, as opposed to point-by-point with a laser beam such as in scanning LIDAR systems. Time-of-flight camera products for civil applications began to emerge around 2000, as the semiconductor processes allowed the production of components fast enough for such devices. The systems cover ranges of a few centimeters up to several kilometers.

Types of devices Several different technologies for time-of-flight cameras have been developed.

RF-modulated light sources with phase detectors Photonic Mixer Devices (PMD), the Swiss Ranger, and CanestaVision work by modulating the outgoing beam with an RF carrier, then measuring the phase shift of that carrier on the receiver side. This approach has a modular error challenge: measured ranges are modulo the RF carrier wavelength. The Swiss Ranger is a compact, short-range device, with ranges of 5 or 10 meters and a resolution of 176 x 144 pixels. With phase unwrapping algorithms, the maximum uniqueness range can be increased. The PMD can provide ranges up to 60 m. Illumination is pulsed LEDs rather than a laser. More recent CW-ToF camera systems illuminate the scene with high-frequency modulated LED light and analyze the phase shift of the returning signal at each pixel to compute depth. For example, in traffic enforcement applications, retroreflective surfaces such as license plates and vehicle reflectors generate strong return signals that are used to construct depth images over time. These images allow tracking of vehicle positions in 3D space and calculation of speed by applying regression analysis to the position-time data. Unlike conventional RADAR, this method measures speed along the vehicle's true direction of travel and is independent of the vehicle’s distance and angle relative to the camera. In some continuous-wave ToF systems, depth images captured over successive time intervals are used to estimate the 3D positions of moving objects, such as vehicles. The system tracks multiple retroreflective points across consecutive frames and reconstructs the object’s trajectory through 3D space. By applying regression analysis to the change in position over time, the system accurately determines the object's speed along its path of travel. Unlike conventional RADAR, this approach minimizes errors associated with distance and angle to the target. CanestaVision developer Canesta was purchased by Microsoft in 2010. The Kinect2 for Xbox One was based on ToF technology from Canesta.

Range gated imagers These devices have a built-in shutter in the image sensor that opens and closes at the same rate as the light pulses are sent out. Most time-of-flight 3D sensors are based on this principle invented by Medina. Because part of every returning pulse is blocked by the shutter according to its time of arrival, the amount of light received relates to the distance the pulse has traveled. The distance can be calculated using the equation, z = R (S2 − S1) / 2(S1 + S2) + R / 2 for an ideal camera. R is the camera range, determined by the round trip of the light pulse, S1 the amount of the light pulse that is received, and S2 the amount of the light pulse that is blocked. The ZCam by 3DV Systems is a range-gated system. Microsoft purchased 3DV in 2009. Microsoft's second-generation Kinect sensor was developed using knowledge gained from Canesta and 3DV Systems. Similar principles are used in the ToF camera line developed by the Fraunhofer Institute of Microelectronic Circuits and Systems and TriDiCam. These cameras employ photodetectors with a fast electronic shutter. The depth resolution of ToF cameras can be improved with ultra-fast gating intensified CCD cameras. These cameras provide gating times down to 200ps and enable ToF setup with sub-millimeter depth resolution. Range gated imagers can also be used in 2D imaging to suppress anything outside a specified distance range, such as to see through fog. A pulsed laser provides illumination, and an optical gate allows light to reach the imager only during the desired time period.

Direct Time-of-Flight imagers These devices measure the direct time-of-flight required for a single laser pulse to leave the camera and reflect back onto the focal plane array. Also known as "trigger mode", the 3D images captured using this methodology image complete spatial and temporal data, recording full 3D scenes with single laser pulse. This allows rapid acquisition and rapid real-time processing of scene information. For time-sensitive autonomous operations, this approach has been demonstrated for autonomous space testing and operation such as used on the OSIRIS-REx Bennu asteroid sample and return mission and autonomous helicopter landing. Advanced Scientific Concepts, Inc. provides application specific (e.g. aerial, automotive, space) Direct TOF vision systems known as 3D Flash LIDAR cameras. Their approach utilizes InGaAs Avalanche Photo Diode (APD) or PIN photodetector arrays capable of imaging laser pulse in the 980 nm to 1600 nm wavelengths.

Components A time-of-flight camera consists of the following components:

… excerpt ends here. Continue reading the full article.

Illustrations

Time-of-flight camera: Time of flight of a light pulse reflecting off a target
Time of flight of a light pulse reflecting off a target
Time-of-flight camera: Principle of operation of a time-of-flight camera:In the pulsed method (1), the distance, d = .mw-parser-output .sfrac{white-space:nowrap}.mw-parser-output .sfrac.tion,.mw-parser-output .sfrac .tion{display:inline-block;vertical-align:-0.5em;font-size:85%;text-align:center;margin-left:.1em;margin-right:.1em}.mw-parser-output .sfrac .num{display:block;border-bottom:1px solid}.mw-parser-output .sfrac .den{display:block;line-height:1.5em}.mw-parser-output .sr-only{border:0;clip:rect(0,0,0,0);clip-path:polygon(0px 0px,0px 0px,0px 0px);height:1px;margin:-1px;overflow:hidden;padding:0;position:absolute;width:1px}⁠c t/2⁠ ⁠q2/q1 + q2⁠ , where c is the speed of light, t is the length of the pulse, q1 is the accumulated charge in the pixel when light is emitted and q2 is the accumulated charge when it is not.In the continuous-wave method (2), d = ⁠c t/2π ⁠ arctan ⁠q3 - q4/q1 - q2⁠ .[18]
Principle of operation of a time-of-flight camera:In the pulsed method (1), the distance, d = .mw-parser-output .sfrac{white-space:nowrap}.mw-parser-output .sfrac.tion,.mw-parser-output .sfrac .tion{display:inline-block;vertical-align:-0.5em;font-size:85%;text-align:center;margin-left:.1em;margin-right:.1em}.mw-parser-output .sfrac .num{display:block;border-bottom:1px solid}.mw-parser-output .sfrac .den{display:block;line-height:1.5em}.mw-parser-output .sr-only{border:0;clip:rect(0,0,0,0);clip-path:polygon(0px 0px,0px 0px,0px 0px);height:1px;margin:-1px;overflow:hidden;padding:0;position:absolute;width:1px}⁠c t/2⁠ ⁠q2/q1 + q2⁠ , where c is the speed of light, t is the length of the pulse, q1 is the accumulated charge in the pixel when light is emitted and q2 is the accumulated charge when it is not.In the continuous-wave method (2), d = ⁠c t/2π ⁠ arctan ⁠q3 - q4/q1 - q2⁠ .[18]
Time-of-flight camera: Diagrams illustrating the principle of a time-of-flight camera with analog timing
Diagrams illustrating the principle of a time-of-flight camera with analog timing
Time-of-flight camera: Range image of a human face captured with a time-of-flight camera (artist’s depiction)
Range image of a human face captured with a time-of-flight camera (artist’s depiction)
Time-of-flight camera: The Samsung Galaxy S20 Ultra features three rear-facing camera lenses and a ToF camera.
The Samsung Galaxy S20 Ultra features three rear-facing camera lenses and a ToF camera.

Worked examples

Example 1 — a first encounter with Time-of-flight camera

Start with the simplest possible case. Write down what Time-of-flight camera claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In computer science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Time-of-flight camera before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Time-of-flight camera ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Time-of-flight camera

In research
Time-of-flight camera appears in computer science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Time-of-flight camera in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Time-of-flight camera is common in secondary-school and first-year university syllabi. It links to neighbouring topics Digital cameras, Image sensor technology in computer vision, so understanding it makes those chapters shorter.
In everyday life
Look for Time-of-flight camera outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.
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How to study Time-of-flight camera in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Time-of-flight camera means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Time-of-flight camera out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Time-of-flight camera in simple terms?

A time-of-flight camera (ToF camera), also known as time-of-flight sensor (ToF sensor), is a range imaging camera system for measuring distances between the camera and the subject for each point of the image based on time-of-flight, the round trip time of an artificial light signal, as provided by…

Why does Time-of-flight camera matter?

Because it connects several computer science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Time-of-flight camera?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Time-of-flight camera.

Tags

  • Digital cameras
  • Image sensor technology in computer vision

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