Comparatif Duel : EZVIZ C6 2K+ vs Aqara Caméra Hub G3

Ezviz has equipped its camera with a 4 megapixel sensor and thus allows it to capture images up to 2540 x 1440 pixels. Opposite, the Camera Hub G3 is limited to a definition of 2304 x 1296 pixels with its 3 megapixel sensor, but offers a slightly larger field of vision: 110° diagonally, once morest 92°. Both models are of course equipped with infrared vision for the night, and we will add that Ezviz provides an HDR mode to limit backlighting if the C6 2K+ is installed facing a window.

By day

Aqara Camera Hub G3


Ezviz C6 2K+

Despite its wider field of view, the Aqara camera offers slightly less distorted images and we note better exposure of our test scene. The C6 2K+ displays blocked blacks. If we stop at the level of detail, the two cameras are however very close and make it possible to easily distinguish the main features of the faces on our column of portraits.

By night

As soon as the lights go out, the two cameras switch to infrared vision, following 3 seconds for the Camera Hub G3, and twice that for the C6 2K+. The Aqara model once more offers better rendering of dark areas, but the light areas are a bit overexposed in return, so that we can barely distinguish the features on the first face of our column of portraits. Despite elements that are difficult to read (such as the cover of our book), the Ezviz camera generally does much better with the portraits of our test scene.



Aqara Camera Hub G3


Ezviz C6 2K+

These results were also confirmed during our night identification test, the C6 2K+ having enabled us to identify an individual up to 4 meters away, once morest just over 2.5 meters for its competitor. Aqara’s artificial intelligence does not do much better and has not recognized a face more than 2 meters away, still at night. In terms of motion detection, it is still the Ezviz camera that wins with a range of regarding 9 meters. By detecting activities up to 8.5 meters, the Camera Hub G3 does not, however, come far behind and it should be added that the two models offer similar results with the detection of human shapes.

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