Multi-Camera Object Detection for Incomplete Zoomed Images

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Solution Overview

Problem

Existing electronic devices struggle to accurately analyze images and identify objects when there is insufficient information, such as when images are taken with zoomed-in cameras, missing parts of the object, leading to incomplete object recognition.

Innovation Solution

The electronic device uses multiple cameras, one in zoom mode and one in normal mode, to obtain images, detect objects, and perform object recognition by correlating the images to accurately identify objects even when zoomed-in images are incomplete.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If a camera operates in zoom mode to capture images of objects, then the magnification and detail of the object is improved, but the completeness of the object information is lost because parts of the object are missed

Engineering Contradiction:
Improveobject detection accuracyVSAvoidobject information completeness
Core Design Contradiction:
Measurement precisionVSLoss of information

Solution Approach 1:

The patent divides the imaging function into two segments: a first camera for capturing zoomed-in images and a second camera for capturing normal images. By segmenting the imaging task between two cameras with different focal lengths, the system can simultaneously obtain both detailed views and complete object information, resolving the contradiction between magnification precision and information completeness.

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The processor acts as an intermediary that receives images from both cameras and performs object detection and recognition by analyzing both the zoomed-in first image and the complete second image. This intermediary processing enables the system to leverage the advantages of both imaging modes to achieve both detailed detection and complete object identification.

Inventive Principle:
Principle #24Intermediary (Mediator)

2Reliability

If multiple cameras are used to obtain both zoomed-in and normal images, then the object recognition accuracy is improved, but the device complexity increases

Engineering Contradiction:
Improveobject recognition accuracyVSAvoidcamera system complexity
Core Design Contradiction:
ReliabilityVSDevice complexity

Solution Approach 1:

The patent implements a multi-functional camera system where both the first and second cameras serve dual purposes: capturing images for object detection and providing reference information for the processor. The system uses the same hardware infrastructure for both imaging modes, allowing the cameras to perform multiple functions (detailed imaging and complete imaging) without requiring entirely separate systems, thus managing complexity while improving reliability.

Inventive Principle:
Principle #6Universality (Multi-functionality)

Data Source

PatentUS12452536B2Electronic device and electronic device control method
Publication Date: 2025.10.21 SAMSUNG ELECTRONICS CO LTD
  • US12452536B2 patent drawing
  • US12452536B2 patent drawing
  • US12452536B2 patent drawing

AI summary

An electronic device and a controlling method thereof are provided. The electronic device includes a display, a first camera, a second camera, memory storing one or more computer programs, and one or more processors communicatively coupled to the display, the first camera, the second camera, and the memory, wherein the one or more computer programs include computer-executable instructions that, when executed by the one or more processors, cause the electronic device to, obtain a first image through the first camera operating in a zoom mode, control the display to display the first image, obtain a second image through the second camera operating in a normal mode, identify a third image of the first camera in the normal mode corresponding to the first image based on a zoom-in ratio in the zoom mode, by detecting an object included in the second image, obtain location information regarding the detected object in the second image, based on a relative location between the second image and the third image, obtain location information of the object in the third image corresponding to the location information obtained from the second image, and, based on the location information of the object, detect the object in the first image.