Image depth estimation method and device, electronic equipment and storage medium

By performing feature extraction and parallax information processing on the video data collected by the binocular camera, the accuracy problem of the binocular depth estimation method in complex scenarios is solved, and high-quality depth map generation is achieved to meet the needs of various application scenarios.

CN120047510APending Publication Date: 2025-05-27ORIENTAL POWER HOLDINGS LTD
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Patent Information

Application Number
CN202311579558.5
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2023-11-24
Publication Date
2025-05-27

AI Technical Summary

Technical Problem

The existing binocular depth estimation method is prone to pixel point matching errors in complex image acquisition scenarios, resulting in the output depth map being inaccurate enough and cannot meet the needs of depth maps in various application scenarios.

Method used

By preprocessing one frame of binocular images in the video data collected by the binocular camera, feature extraction is performed on the left and right eye images, feature similarity information is calculated, and target parallax information is determined based on the reference parallax information of the previous binocular image, and target depth information is finally obtained.

Benefits of technology

It improves the accuracy and density of depth maps, and meets the needs of depth maps in various application scenarios such as three-dimensional reconstruction, 3D content generation, and virtual reality.

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Abstract

The invention relates to the technical field of artificial intelligence, in particular to an image depth estimation method and device, electronic equipment and a storage medium. The method comprises the following steps: extracting a frame of binocular image from video data acquired by a binocular camera, and preprocessing a left eye image and a right eye image in the frame of binocular image; performing feature extraction on the preprocessed left eye image and right eye image to obtain corresponding left image features and right image features, and performing pixel-level similarity calculation on the left image features and the right image features to obtain corresponding feature similarity information; determining target parallax information of the frame of binocular image based on the feature similarity information and the image features in combination with reference parallax information of a previous frame of binocular image of the frame of binocular image; and obtaining target depth information based on the target parallax information of the frame of binocular image in combination with camera parameters of the binocular camera. The effect of the generated depth map is improved, so that the requirements of various application scenes of the depth map are met.
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