Camera Composition Guidance via Scene Analysis and Depth Mapping
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Solution Overview
Problem
Users, especially amateur photographers, often capture images of monuments, scenes, and events that are not of optimal quality due to issues like asymmetry, objects being out-of-focus, and lack of depth representation, as they are unaware of the composition and camera settings required for better images.
Innovation Solution
A camera-equipped device with an image analyzer application that identifies objects and attributes in the scene, provides suggestions through various formats (text, image overlays, audio) to adjust the camera's position and settings for improved composition and quality, using pre-defined rules to compute a composition score and offer corrective actions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If users take pictures without composition guidance, then the operation is simple and quick, but the image composition quality deteriorates (asymmetry, skewed buildings, poor framing)
Solution Approach 1:
The system performs preliminary analysis of the scene using depth maps and object detection before the user captures the image. It pre-calculates composition guidance, identifies objects of interest, and determines optimal framing in advance, allowing the user to simply follow the guidance without complex manual adjustments.
Solution Approach 2:
The system provides real-time feedback to the user about composition quality by analyzing the current frame, comparing it against ideal composition rules, and displaying actionable guidance. This feedback loop continues until the user achieves satisfactory composition, transforming an otherwise subjective skill into an objective, guided process.
2Manufacturing precision
If users manually adjust camera settings for optimal composition, then image quality improves, but the ease of operation deteriorates (requires expertise and time)
Solution Approach 1:
The system performs automatic scene analysis, object detection, and composition evaluation without requiring user expertise. The camera device itself analyzes the scene using its sensors and processors, generating composition guidance automatically based on pre-programmed rules and depth information, freeing the user from needing photographic knowledge.
Solution Approach 2:
The system replaces manual mechanical adjustment of camera settings with automated electronic analysis and guidance. Instead of the user physically adjusting the camera based on experience, electronic sensors capture depth maps and object data, which are processed to generate composition recommendations that the user can follow.
3Manufacturing precision
If the system provides detailed composition guidance, then the image quality improves, but the loss of time increases (analysis and processing time)
Solution Approach 1:
The system focuses on providing only the most critical composition guidance needed for immediate improvement rather than analyzing every possible aspect of the scene. It identifies key objects and primary composition issues, providing targeted feedback that addresses the most significant problems first, allowing quick corrections without exhaustive analysis.
Solution Approach 2:
The system continuously pre-processes scene data in the background, maintaining ready-to-use composition guidance as the user moves the camera. Depth maps and object detections are generated continuously, so when the user intends to capture an image, the composition analysis is already prepared or can be quickly computed from recently captured frames.
4Measurement precision
If the system uses depth attributes for composition analysis, then the measurement precision improves, but the device complexity increases (requires depth sensing)
Solution Approach 1:
The system uses the existing camera lens and image sensor to serve multiple functions: capturing both the visual image and depth information. By analyzing focus characteristics, blur gradients, and optical properties of the captured image, the system extracts depth attributes without requiring separate depth-sensing hardware, making the solution applicable to standard cameras.
Solution Approach 2:
The system uses the optical properties of the camera lens as an intermediary to derive depth information. Instead of directly measuring depth with specialized sensors, it analyzes the optical characteristics of the captured image (such as focus distribution and blur patterns) to infer depth relationships between objects, using the lens itself as the measurement tool.
Data Source
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AI summary
A method, computer readable medium and an apparatus are presented for providing composition and position guidance for a camera. One method includes detecting an image received on a capturing device. The image is analyzed to identify objects and determine attributes of the objects. Suggestions are provided to adjust at least one of position or setting of the capturing device in accordance to rules, based on the analysis of the image. Adjustment of the capturing device based on the suggestions provided, are detected and used to receive an adjusted image. The adjusted image is captured by the capturing device.