Autofocus (AF) is a technology in cameras that automatically determines where the focus point should be in an image and then adjusts the lens to focus on that point. Instead of manually focusing by turning the lens, as was previously common, autofocus lets the camera perform this process on its own.
The purpose of autofocus is to focus quickly and accurately, allowing the photographer to concentrate on capturing the moment rather than on technical settings. Autofocus works by using sensors and algorithms that calculate the distance between the camera and the subject, using light, contrast and sometimes even face and eye recognition technology to determine which part of the image should be in focus.
In the early days of digital photography, most cameras, especially digital single-lens reflex cameras (DSLRs), used single phase-detection autofocus (for DSLRs) and contrast-detection autofocus (for compact cameras).
Phase detection in SLR cameras was already known for its speed, but the number of autofocus points was limited and usually in the center of the image. Contrast detection, commonly used in early digital compact cameras, was slow and less accurate, especially in low light.
Cameras often only had 3 to 9 AF points, and they were usually concentrated in the center of the frame and autofocus was limited to focusing on a specific point that you had to select yourself. The camera did not automatically track the subject as it moved.
Autofocus had great difficulty focusing correctly in poor lighting conditions, especially with contrast detection. For example, the Canon EOS 10D (2003) was a popular DSLR that used six autofocus points, all placed in the center of the frame. This was fast and accurate for its time, but compared to modern standards the AF system was limited, especially with fast subjects.
Ten years ago, cameras had more autofocus points, which were also distributed over a larger part of the frame. This made it easier to keep subjects in focus, even when they were not in the center of the frame.
Cameras often had 51 or more AF points, such as the Nikon D7200, and these were better distributed across the frame. Autofocus now began tracking moving subjects, although these systems were not yet as sophisticated as today's real-time tracking. Especially in mirrorless cameras and higher DSLR models, facial recognition started to emerge, which helped with portraits.
The Canon EOS 70D (2013) introduced Canon's Dual Pixel AF, which was a major breakthrough for both photography and videography. This system used phase detection directly on the sensor, which significantly improved the accuracy and speed of autofocus, especially during filming and when shooting in live view mode.
The technology surrounding autofocus (AF) has made enormous leaps in recent years, especially in modern system cameras. These developments have drastically improved the way we photograph and film. Below is an overview of the most innovative autofocus techniques and how they have been applied in practice.
1. Phase Detection AF (Phase Detection Autofocus)
Phase detection autofocus is now increasingly used in system cameras. This technique works by splitting light coming through the lens into two separate beams and measuring the distance between the two. This makes it possible to calculate the focusing distance very quickly and immediately send the lens motor in the correct direction, resulting in lightning-fast focus.
The biggest advantage of phase-detection AF is the speed with which it focuses, especially with moving subjects or low-contrast situations. This makes it ideal for sports photography and fast action. Although this technique may be slightly less accurate than contrast detection in situations with low light or extreme detail, it is very effective in everyday applications.
Practical example:
The Sony Alpha 7 IV features a phase detection system that works over almost the entire image sensor surface. This means that it can focus not only in the center of the image, but also at the edges. This ensures faster and more reliable focusing with subjects that are not always in the center of the frame.
2. Contrast detection AF
Contrast-detection AF works by focusing on the area in the image with the greatest contrast. When the camera senses that contrast is increasing in a certain part of the photo, it will continue focusing until maximum contrast is reached, meaning the subject is in focus.
Contrast detection is often more accurate than phase detection, especially with stationary subjects or in situations where a lot of detail is needed, such as macro photography or portrait photography. The downside is that it can sometimes be slower, as the camera has to cycle through multiple focus points to find the sharpest point.
Practical example:
The Panasonic Lumix S5 uses an advanced contrast-detection AF system, which is especially useful when photographing stationary subjects such as landscapes or studio portraits. This ensures razor-sharp images without loss of detail.
3. Hybrid AF: A combination of phase and contrast detection
Hybrid autofocus combines the best of both worlds: phase detection for speed and contrast detection for precision. In this system, phase detection is used to bring the lens near the point of focus, and then contrast detection is used to fine-tune the focus.
This system ensures fast focusing without sacrificing accuracy. It can work effectively in different lighting conditions and with different types of subjects, from fast-paced action to detailed still life.
Practical example:
The Fujifilm X-T5 uses a hybrid AF system suitable for versatile photography. This camera can track fast-moving subjects, such as in street photography, as well as provide very precise focusing for portraits and landscapes.
4. Eye Autofocus (Eye AF)
Eye Autofocus is a technology specially developed for portrait photography and photographing people. This system recognizes a person's eyes in the image and automatically focuses on them. This is crucial because in portrait photography the model's eyes are often the most important element, and out-of-focus eyes can ruin the image even if the rest of the face is in focus.
What makes Eye AF so revolutionary is that it continues to work even in motion. This means that even if the model moves or the photographer himself moves, the camera will automatically continue to focus on the eyes. This provides unprecedented precision and makes it easier than ever to shoot razor-sharp portraits.
Practical example:
Sony's Eye AF in the Sony A7R IV is leading. Even with fast movements or when the model's eyes are partially covered, the camera remains able to focus accurately. This has taken portrait photography and even wedding photography to the next level.
5. Animal and Bird Recognition AF
Animal and bird recognition autofocus builds on the techniques of Eye AF, but has been specially developed for wildlife photographers. Instead of human eyes, the system recognizes the eyes and faces of animals. This is particularly useful because animals often move unpredictably and are fast.
Traditional autofocus would struggle to maintain focus in such conditions, but animal and bird recognition allows the camera to continuously focus on the animal, even when it is moving or its face is not fully visible.
Practical example:
The Canon EOS R5 has an impressive AF system that is specially designed to recognize animals and birds. This allows wildlife photographers to capture fast-moving animals with a precision that was previously not possible. This function is a game changer, especially for bird watchers, who have to deal with fast-flying and often small subjects.
6. Deep Learning and AI-based Autofocus
The rise of deep learning and AI has led to autofocus systems that are becoming increasingly smarter. These systems learn from huge data sets and adapt to different situations. For example, they can recognize faces, objects or animals and focus on them automatically, without the photographer having to intervene manually. In addition, they can interpret and anticipate scenarios such as rapid movements or changing lighting conditions in real time.
This technology is especially useful in situations where rapid changes occur, such as sports photography or photographing children and animals, where unpredictable movements are common.
Practical example:
The Nikon Z9 uses AI-controlled autofocus. This system continuously learns and recognizes a wide range of subjects, from faces to vehicles. The autofocus automatically adjusts depending on the environment and subject, which gives the photographer a huge advantage when shooting fast and complex scenes.
7. Real-time Tracking
Real-time tracking is an autofocus technique specifically aimed at tracking moving subjects. This system combines technologies such as facial and eye recognition with object recognition to continuously maintain focus on a subject moving within the frame.
This is especially useful when photographing sports or making videos, where the subject is often moving quickly. The camera continues to focus in real time even if the subject suddenly changes direction or if the photographer moves.
Practical example:
The Fujifilm X-T5 provides excellent real-time tracking, meaning focus automatically stays on the subject even as it moves quickly through the frame. This is especially useful when filming dynamic scenes, such as sports or action.
8. Focus Bracketing and Focus Stacking
Focus bracketing is a technique in which the camera takes multiple photos with different focus points. These images can then be combined (focus stacking) to create one image with an extremely large depth of field. This is especially useful in macro photography, where it can be difficult to get an entire scene in focus due to the limited depth of field.
In macro photography or when photographing landscapes where a large depth of field is required, this technique ensures razor-sharp images from foreground to background.
Practical example:
Especially with macro photography you have to deal with a small depth of field. The automatic Focus Bracketing of the Sony Alpha 7RV allows you to capture more depth in perfect focus without moving the camera, and then get the image even sharper in post-production.
