What Is a ToF Camera? How Depth Sensors Work in Smartphones

ToF camera is a depth sensor that determines the distance to objects based on the time of flight of light. The smartphone emits a short infrared light pulse, captures its reflection, and calculates the distance to a surface based on the delay. This allows the device to capture not just a regular image but also depth information about the scene.

What Is a ToF Camera and Why Do Smartphones Need It?

A ToF camera, or Time of Flight camera, is a sensor that measures the distance to objects using light. The technology's name literally means "time of flight": the sensor evaluates how long it takes for a light signal to travel to an object, reflect off it, and return.

In smartphones, the ToF sensor typically works in the infrared spectrum, invisible to the human eye. The device illuminates the scene with infrared light and then registers the reflected signal. Since the speed of light is known, the electronics can calculate the distance to different parts of the scene.

The main difference between a ToF sensor and a regular camera lies in the type of information they capture. A standard camera records brightness, color, and image details, creating a two-dimensional shot. The ToF camera additionally determines the distance to objects and helps build a depth map.

This map represents the scene not only by width and height, but also by how far objects are from the smartphone. For example, the system can identify that a person's face is closer, the background is farther, and an object in between occupies an intermediate position.

This information is useful in several scenarios. The smartphone can better separate the main subject from the background for portrait shots, estimate object sizes, detect surfaces for augmented reality, and create simple 3D models of spaces.

However, the ToF camera is rarely used as a standalone module for taking photos. It works alongside the main camera and software algorithms, supplementing regular images with distance data. Because of this, the sensor is often called a depth camera or depth sensor.

How Does a ToF Camera Work: Measuring Distance by Time of Flight

The operating principle of a ToF camera is straightforward: if you know the speed of light, you can determine the distance to an object by the time it takes for a light signal to travel to it and back. In practice, these time intervals are extremely short, so all processing is handled electronically with high precision.

How Infrared Light Reflects Off Objects

The ToF module consists of an infrared light source and a sensitive sensor. The smartphone emits invisible light onto surrounding objects. Some of this light reflects off surfaces and returns to the sensor.

Different areas of the scene are at varying distances from the device, so the reflected signals return at different times. Light from a nearby object arrives a bit sooner than light reflected from a wall or background object.

The properties of surfaces also impact measurement results. Light and highly reflective materials usually return a stronger signal, while dark, transparent, or very glossy surfaces can complicate detection.

How the Sensor Calculates Distance

After sending the light signal, the electronics measure the return delay. Since the light travels from the smartphone to the object and back, the total distance is divided by two.

Simply put, the calculation is: distance equals the speed of light multiplied by the signal's travel time, divided by two. Because the time intervals are so short, the ToF sensor requires specialized electronics.

Some systems use modulated infrared light instead of short pulses. In this case, distance is determined by the phase shift of the reflected signal compared to the original. For the user, there's no practical difference: the output is still an estimation of the distance to the surface.

How Depth Maps Are Created

The ToF camera measures distances not just to a single point, but to many areas of the scene at once. Each sensor element receives its own depth value. After processing, the smartphone assembles a map where the approximate distance to the camera is known for each area.

This results in a kind of three-dimensional representation of space. The system understands which objects are closer, which are farther, and how their positions vary in depth.

The depth map is then combined with the main camera's image. At this stage, software algorithms can more accurately determine object boundaries, analyze spatial shapes, and use the data for photography, augmented reality, or 3D scanning.

What Is the ToF Sensor Used for in Smartphones?

The ToF sensor is needed when a standard two-dimensional image isn't enough. It adds distance data so the camera and apps can better interpret scene shapes and object positions relative to each other.

Portrait Mode and Foreground-Background Separation

One of the most obvious uses of the ToF camera is determining depth for portrait shots. The smartphone must identify where the person is, their outline, and how far the background is.

The depth map helps distinguish between foreground and background more precisely. Software can then blur the background while keeping the face, hair, and clothes sharp. Depth information is especially useful in complex scenes where the background color is similar to the subject.

However, the quality of portrait mode depends not only on the ToF sensor. Modern smartphones can estimate depth using multiple cameras and computer vision algorithms, so a dedicated depth sensor isn't always essential.

Autofocus and Low-Light Shooting

Distance information can help the camera quickly determine the subject's location. The ToF sensor doesn't need to analyze image contrast to estimate distance, giving the system extra data for focusing.

This advantage is most noticeable in low-light situations, where a standard camera struggles to discern scene details. The ToF module's infrared emission works independently of visible light, so the sensor can measure depth even when the main camera's image lacks contrast.

However, whether the ToF sensor assists autofocus depends on the smartphone's camera design. Some devices use other technologies, like phase detection or laser focus.

3D Scanning of Objects and Spaces

Since the ToF camera captures many distance values at once, its data can be used to create three-dimensional representations of objects or rooms. The user moves the smartphone around the subject, and the software combines consecutive depth maps into a single model.

Mobile ToF sensors usually aren't accurate enough for professional industrial 3D scanning, but their capabilities are sufficient for everyday tasks. For example, the technology can estimate an object's shape, scan part of a room, or supply data for spatial apps.

Augmented Reality and Measuring Dimensions

For augmented reality, the smartphone must accurately detect real-world surfaces. If a virtual object should sit on a floor or table, the system has to determine the surface's position and distance.

The depth map helps the device quickly recognize surrounding geometry, allowing virtual objects to be placed more realistically among furniture, walls, and other items.

The same principle applies to apps for measuring distance and size. The smartphone evaluates the depth of several points and calculates approximate length, height, or distance between objects based on their positions. While these measurements are convenient for everyday use, they don't replace professional measuring tools where high accuracy is needed.

ToF vs. LiDAR: What's the Difference?

ToF and LiDAR both measure distance to objects using light, which is why they're often seen as the same thing. However, their designs and data acquisition methods can differ.

What ToF and LiDAR Have in Common

Both technologies use the Time of Flight principle: a light source emits a signal, which reflects off an object and returns to the sensor. The system determines the distance by measuring how long the signal travels.

Both ToF cameras and LiDAR can create depth maps, help the smartphone interpret spatial geometry, detect surfaces, and work with augmented reality. In both cases, infrared light invisible to the human eye is usually used.

For a detailed explanation of laser scanning in smartphones and cars, see How LiDAR Works: Scanning Principles in Smartphones and Cars.

How Their Scanning Methods Differ

A classic ToF camera typically illuminates a large part of the scene, measuring depth for many points at once using a sensor matrix. This enables the depth map to be formed quickly, without mechanical scanning.

LiDAR is a broader concept. Such systems may sequentially send laser pulses in different directions or use multiple points simultaneously. The result is a point cloud-a set of coordinates describing the surrounding space.

Because of design differences, LiDAR can offer greater range and more detailed spatial measurement, especially in specialized systems. This is why the technology is used not only in smartphones, but also in vehicles, robotics, surveying, and industrial equipment.

Which Technology Is Better for Smartphones?

It's not possible to declare one technology universally better-the best choice depends on the task. A compact ToF sensor is well-suited for near-field depth detection, portrait photography, autofocus, and simple AR applications.

LiDAR offers advantages for more detailed space scanning and for confidently measuring distances to many surfaces. However, the more complex system may take up extra space, consume more power, and increase device cost.

For typical mobile photography, the user may not notice much difference. The result's quality largely depends on software processing, the sensor's specs, and how well the manufacturer integrates depth data with the main camera.

Is a ToF Camera Necessary in Modern Smartphones?

Having a dedicated ToF camera isn't a must-have feature for a good smartphone. While it can improve scene depth processing, many manufacturers now solve these tasks using multiple regular cameras, phase-detection autofocus, and computer vision algorithms.

For everyday photography, users often don't even notice whether their smartphone has a ToF sensor. Image quality depends more on the main camera, optics, sensor size, and processing. Even portrait mode can work accurately without a separate depth sensor.

ToF is most useful when the smartphone truly needs to measure space: for augmented reality, distance measurement, depth mapping, and basic 3D scanning. In these cases, hardware-based distance data reduces the system's reliance on algorithmic guesses.

When choosing a smartphone, paying extra solely for a ToF camera usually isn't worth it. If photography is the priority, it's better to evaluate the main camera quality and image processing. For AR, room scanning, and other spatial tasks, a dedicated depth sensor can be a real advantage.

Ultimately, the ToF sensor should be seen not as an independent camera determining smartphone quality, but as an extra tool. Its value depends on how actively the manufacturer uses depth data in the camera and apps.

Conclusion

The ToF camera helps a smartphone determine not only what's in front of the lens, but also how far objects are. The sensor uses infrared light and measures its travel time to and from surfaces, then creates a depth map of the scene.

This data is useful for portrait shots, autofocus, augmented reality, distance measurement, and simple 3D scanning. A dedicated ToF sensor is not mandatory for a good camera, as many modern smartphones gather depth information with multiple cameras and software algorithms.

If you want a smartphone primarily for regular photography, ToF support shouldn't be the main selection criterion. But for AR apps, spatial work, or 3D scanning, a dedicated depth sensor can provide a real edge.