Dual-Camera Object Tracking for Small HDR Preview Targets
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Solution Overview
Problem
Existing electronic devices struggle to perform high-dynamic-range photographing or video recording on small objects in a preview image, as users cannot select and lock them due to their small size.
Innovation Solution
The electronic device uses a second camera with a higher resolution to identify and track target objects within a preview image, displaying identifiers for these objects, allowing users to select and lock them for high-dynamic-range recording without manual selection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a user selects a target object in a preview image to perform high-dynamic-range photographing, then the photographing function can be activated, but small objects cannot be selected and locked due to their small size in the preview image
Solution Approach 1:
The system segments the object identification process into two stages: first, the processor identifies candidate objects in the preview image; second, it presents these identified objects to the user for confirmation. This segmentation allows the system to handle small objects that are difficult for users to select directly, as the processor performs the initial identification work.
Solution Approach 2:
The processor acts as an intermediary between the camera system and the user. It receives the preview image, identifies target objects automatically, and presents them to the user for selection confirmation. This intermediary role bridges the gap between automatic detection and user control, enabling high-dynamic-range photographing for objects that would otherwise be too small to select manually.
2Speed
If the preview image resolution is kept low for fast display, then display performance is improved, but the ability to identify and lock small target objects deteriorates
Solution Approach 1:
The system performs partial high-resolution processing only for identified target objects rather than processing the entire preview image at high resolution. The processor identifies objects in the preview image and then acquires corresponding high-resolution images only for those specific targets, avoiding the need to display the entire high-resolution image and thus maintaining fast display performance while achieving accurate object identification.
Solution Approach 2:
The system transitions from a single-resolution preview image to a multi-resolution approach. It maintains the low-resolution preview image for fast display while acquiring and processing separate high-resolution images for identified target objects. This dimensional change in resolution handling allows simultaneous achievement of fast display and accurate object identification.
Data Source
AI summary
An object tracking method includes: acquiring a first image through a second camera in a case that a preview image acquired through a first camera is displayed, where the preview image and the first image include a plurality of objects, the plurality of objects are images of a plurality of first physical objects, and a resolution of the first image is greater than a resolution of the preview image; displaying, according to the first image and in the preview image, at least one identifier used for indicating M target object(s) in the plurality of objects in the preview image, M being a positive integer; receiving a first input for a first object in the M target object(s) in the preview image; and tracking a physical object corresponding to the first object and displaying an image of the physical object corresponding to the first object in response to the first input.