We subjected the Xiaomi 12S Ultra to our rigorous SBMARK Selfie test suite to measure its performance in photos and videos from an end-user perspective. This article analyzes how the device performed in a variety of tests and several common use cases and aims to highlight the most important results of our tests with an excerpt of the data captured.
Overview
Main specifications of the front camera:
- 32MP sensor
- Lens with f/2.4 aperture
- Videos: 1080p/30fps
Pros
- Accurate exposure in bright light and indoors for photo and video bots
- Nice color in bright light and indoor video
- Good detail in the plane of focus
- Low noise levels in photos and videos
Against
- Occasionally inaccurate skin tones, especially in photos
- Rather low contrast in videos
- Fairly shallow depth of field
- Slightly jerky video stabilization when moving during recording
With a SBMARK Selfie score of 114, the Xiaomi 12S Ultra offered a capable front camera for daily selfie photo and video capture, but it didn’t come close to the top of our rankings. It also lagged behind its predecessor Mi 11 Ultra in terms of photography performance. Both stills and video clips showed good exposure and fairly accurate white balance. Texture levels were high even at close range, but a shallow depth of field means Xiaomi isn’t the best option for group selfies. Our testers also found contrast to be slightly low, especially in bright outdoor scenes, and color artifacts, such as hue shift, resulting in an unnatural rendering of the sky.
Xiaomi 12S Ultra Selfie Scores vs Ultra-Premium
This graph compares overall SBMARK Selfie photo and video scores between tested and referenced devices. The average and maximum scores of the price segment are also indicated. The average and maximum scores for each price segment are calculated based on the SBMARK device database.
Trial summary
Learn about SBMARK Selfie Tests: For scoring and analysis, SBMARK engineers capture and evaluate more than 1,500 test images in both controlled laboratory environments as well as outdoor, indoor, and low-light natural scenes using default camera settings front. The photo protocol is designed with the user in mind and is based on typical shooting scenarios, such as close-ups and group selfies. Evaluation is performed by visually inspecting images Cons a natural scene reference and by performing objective measurements on laboratory-acquired graph images under various lighting conditions from 1 to 1,000+ lux and color temperatures from 2,300 K to 6,500 K. For more information about SBMARK Selfie test protocol, please click here. More details on how we rate smartphone cameras can be found here. The following section compiles the key elements of SBMARK’s exhaustive testing and analysis. Full performance evaluations are available upon request. Please contact us on how to receive a full report.
Photo
103
Huawei Mate 50 Pro
Huawei Mate 50 Pro
Xiaomi 12S Ultra Photo vs Ultra-Premium scores
Photo tests analyze image quality attributes such as exposure, color, texture and noise under various lighting conditions. Focus range and the presence of artifacts are also evaluated on all images acquired under controlled laboratory conditions and on real-life images. All of these attributes have a significant impact on the final quality of the images captured with the tested device and can help you understand the main strengths and weaknesses of the camera.
When taking still selfies in Photo mode, the camera produced images with good target exposure and fairly accurate white balance. However, the contrast was limited and as a result faces had a flat appearance and color casts could be seen Cons the background of the scenes. Skin tone rendering also left room for improvement, with inaccuracies in some scenes. Close-up detail was close enough to competitors in the same class, but our testers also noticed some image artifacts, including shifts in hue near cropped image areas.
Xiaomi 12S Ultra – good target exposure and accurate white balance
Exposure
74
Apple iPhone 14 Pro Max
Apple iPhone 14 Pro Max
Color
67
Google Pixel 7 Pro
Google Pixel 7 Pro
Exposure and color are key attributes for technically good images. For exposure, the main attribute evaluated is how bright faces are in various use cases and lighting conditions. Other factors evaluated are contrast and dynamic range, e.g. the ability to make details visible in light and dark areas of the image. Repeatability is also important because it demonstrates the camera’s ability to provide the same rendering when shooting consecutive images.
For color, the image quality attributes analyzed are skin tone rendering, white balance, color shading, and repeatability.
Xiaomi 12S Ultra – low contrast
Huawei Mate 50 Pro – good contrast
Apple iPhone 14 Pro – good contrast
Xiaomi 12S Ultra: inaccurate skin tones
Huawei Mate 50 Pro – acceptable skin tones
Apple iPhone 14 Pro: Accurate skin tones
Focus
60
Huawei Mate 50 Pro
Huawei Mate 50 Pro
Autofocus tests evaluate the accuracy of focusing on the subject’s face, repeatability of accurate focus, and depth of field. While a shallow depth of field can be nice for a single-subject selfie or close-up shot, it can be problematic in specific conditions like group selfies; both situations are tested. Focus accuracy is also evaluated in all real-life images taken, from 30cm to 150cm, and in low-light or outdoor conditions.
Xiaomi 12S Ultra – depth of field
Huawei Mate 50 Pro – depth of field
Apple iPhone 14 Pro – depth of field
Structure
69
Asus ZenFone 7 Pro
Asus ZenFone 7 Pro
Texture tests analyze the level of detail and texture of subjects in images taken in the lab as well as real-life scenarios. For natural shots, particular attention is paid to the level of detail of facial features, such as the eyes. Objective measurements are performed on map images taken under various lighting conditions from 1 to 1000 lux and different types of dynamic range conditions. The charts used are the proprietary SBMARK (DMC) chart and the Dead Leaves chart.
Xiaomi 12S Ultra – detail
Huawei Mate 50 Pro – detail
Apple iPhone 14 Pro – detail
Evolution of the acuity of the texture with the level of illuminance
This graph shows the evolution of texture acuity with lux level for two holding conditions. The sharpness of the texture is measured on the Dead Leaves graph in the Close-up Dead Leaves configuration.
Noise
68
Huawei Mate 50 Pro
Huawei Mate 50 Pro
Noise tests analyze various noise attributes such as intensity, chromaticity, grain, and structure on real-life images as well as graph images captured in the lab. For natural images, special attention is paid to noise on faces, but also to dark areas and high dynamic range conditions. Objective measurements are performed on chart images captured under various conditions from 1 to 1000 lux and different types of dynamic range conditions. The graph used is the SBMARK Dead Leaves graph and standardized measurement as Visual Noise derived from ISO 15739.
Evolution of visual noise with illuminance levels in portable conditions
This graph shows the evolution of the visual noise metric with lux level under palmar conditions. The Visual Noise metric is the average of the Visual Noise measurement across all patches of the Dead Leaves graph in the Close-up Dead Leaves configuration. The SBMARK visual noise measurement is derived from the ISO15739 standard.
Artifacts
82
Google Pixel 7 Pro
Google Pixel 7 Pro
Artifact assessment examines lens shading, chromatic aberrations, distortion measurement on the Dot and MTF graph, and ringing measurements on the SFR graph in the lab. Particular attention is paid to ghosting, quantization, halos and hue variations on the face, among others. The more serious and frequent the artifact, the greater the deduction of points from the score. The main artifacts observed and the corresponding loss of points are listed below.
Major penalties for photographic artifacts
video
132
Apple iPhone 14 Pro Max
Apple iPhone 14 Pro Max
About SBMARK Selfie Video Tests
SBMARK engineers capture and evaluate more than 2 hours of video in controlled lab environments and low natural light scenes, indoors and out, using the default front camera settings. Evaluation consists of visually inspecting natural video taken under various conditions and performing objective measurements on lab-recorded graph video under various conditions from 1 to 1000+ lux and color temperatures from 2,300K to 6,500K.
Xiaomi 12S Ultra Video vs Ultra-Premium scores
Video tests analyze the same image quality attributes as still images, such as exposure, color, texture or noise, as well as temporal aspects such as speed, exposure uniformity and stability, white balance and autofocus transitions.
Target exposure and white balance were good in the 12S Ultra selfie video samples we shot during testing. The camera also captured a good level of texture in video, but our testers observed a somewhat narrow dynamic range that could cause highlights and shadows to clip out, especially in bright and low-light conditions. The video stabilization system was only able to counteract camera shake up to a point, and a shallow depth of field meant backgrounds were mostly blurry.
Exposure
73
Apple iPhone 14 Pro Max
Apple iPhone 14 Pro Max
Color
79
Apple iPhone 14 Pro Max
Apple iPhone 14 Pro Max
Exposure tests evaluate facial brightness and dynamic range, e.g. the ability to make details visible in light and dark areas of the image. The stability and temporal adaptation of the exposure are also analysed. Image quality color analysis examines the rendering of skin tone, white balance, color shading, white balance stability and its adaptation when the light changes.
Xiaomi 12S Ultra: slight cropping but good exposure of the face and white balance
Huawei Mate 50 Pro: good exposure, contrast and white balance
Apple iPhone 14 Pro: good exposure, contrast and white balance
Structure
67
Asus ZenFone 6
Asus ZenFone 6
Texture tests analyze the level of detail and texture of real-life videos as well as graphics videos recorded in the lab. Natural video recordings are evaluated visually, with particular attention to the level of detail of facial features. Objective measurements of card images taken under various conditions from 1 to 1000 lux are performed. The chart used is the Dead Leaves chart.
Evolution of the acuity of the texture with the level of illuminance
This graph shows the evolution of texture acuity with lux level for two holding conditions. The sharpness of the texture is measured on the Dead Leaves graph in the Close-up Dead Leaves configuration.
Noise
71
Xiaomi Mi 11 Ultra
Xiaomi Mi 11 Ultra
Noise tests analyze various noise attributes such as intensity, chromaticity, grain, texture, temporal aspects on real-life video recording, as well as graph videos taken in the lab. Natural videos are evaluated visually, with particular attention to noise on faces. Objective measurements are performed on graph videos recorded under various conditions from 1 to 1000 lux. The graph used is the SBMARK visual noise graph.
Evolution of spatial visual noise with level of illumination
This graph shows the evolution of spatial visual noise with lux level. Spatial visual noise is measured on the visual noise table in the video noise setup. The SBMARK visual noise measurement is derived from the ISO15739 standard.
Time evolution of visual noise with level of illumination
This graph shows the evolution of visual noise over time with lux level. Temporal visual noise is measured on the visual noise table in the video noise setup.
Stabilization
72
Apple iPhone 14 Pro Max
Apple iPhone 14 Pro Max
The stabilization rating tests the device’s ability to stabilize footage using software or hardware technologies such as OIS, EIS, or any other means. The evaluation examines overall residual face and background motion, smoothness, and yellow artifacts, during walking and panning use cases under various lighting conditions. The video below is an excerpt from one of the tested scenes.
Xiaomi 12S Ultra – Noticeable camera shake when walking, loss of background detail
Huawei Mate 50 Pro: slight camera shake when walking, good background detail
Apple iPhone 14 Pro: good stabilization, good background detail
Artifacts
83
Apple iPhone 12 mini
Apple iPhone 12 mini
Artifacts are evaluated with MTF and ringing measurements on the SFR graph in the lab, as well as frame rate measurements using the Universal Timer LED. Natural videos are visually evaluated by paying close attention to artifacts such as quantization, hue shift, and face rendering artifacts, among others. The more severe and frequent the artifact, the more points will be deducted from the score. The main artifacts and the corresponding point loss are listed below
Top penalties for video artifacts
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