Simulated Tracking Shot Generation via 3D Reconstruction
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Solution Overview
Problem
Capturing satisfactory tracking shots, especially with complex subject motion, is challenging for novice photographers due to the difficulty in achieving a blurred background and sharp foreground, particularly in nonlinear motion scenarios.
Innovation Solution
A method and system for generating a simulated tracking shot from an image sequence, where spatially varying blur parameters are derived to blur the background while keeping the foreground unblurred, using 3D reconstruction and virtual cameras to create a physically correct simulation of camera motion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a photographer attempts to capture a tracking shot with complex subject motion, then the sense of subject motion can be captured, but it becomes difficult to achieve a blurred background with sharp foreground
Solution Approach 1:
The patent replaces the mechanical operation of manually tracking a moving subject with a camera with an automated computational system. The system uses image processing algorithms to automatically identify the subject, calculate its motion trajectory, and generate appropriate blur parameters for the background, eliminating the need for photographer skill in executing complex tracking movements.
Solution Approach 2:
The system enables the image itself to guide the blur application process. By automatically detecting the subject and its motion characteristics from the image data, the system determines the blur parameters without requiring external manual intervention or expertise, making the process self-directed and automated.
2Reliability
If manual tracking shot techniques are used, then some motion effect can be achieved, but extensive user expertise is required to achieve satisfactory results
Solution Approach 1:
The patent replaces the need for photographer expertise and manual skill with an automated computational system. The system uses algorithms to perform subject detection, motion analysis, and blur parameter calculation, substituting human skill with machine intelligence that automatically produces professional-quality tracking shots.
Solution Approach 2:
The system creates a computational model of the desired tracking shot effect by analyzing the input image and generating appropriate blur parameters. Instead of requiring the photographer to manually recreate the effect through skillful camera operation, the system copies and simulates the tracking shot outcome through automated image processing.
3Reliability
If automated blur generation is implemented, then tracking shot quality improves, but computational processing complexity increases
Solution Approach 1:
The patent divides the image processing task into distinct segments: subject detection, motion trajectory calculation, and blur parameter generation. By segmenting the computational process, the system manages complexity through modular processing steps, where each segment handles a specific aspect of the tracking shot creation independently.
Solution Approach 2:
The system applies different blur characteristics to different regions of the image based on local motion analysis. By calculating blur parameters specifically for background regions while preserving the sharp foreground subject, the system achieves high-quality tracking shots with targeted processing that reduces overall computational complexity compared to processing the entire image uniformly.
Data Source
AI summary
A simulated tracking shot is generated from an image sequence in which a foreground feature moves relative to a background during capturing of the image sequence. The background is artificially blurred in the simulated tracking shot in a spatially-invariant manner corresponding to foreground motion relative to the background during a time span of the image sequence. The foreground feature can be substantially unblurred relative to a reference image selected from the image sequence. A system to generate the simulated tracking shot can be configured to derive spatially invariant blur kernels for a background portion by reconstructing or estimating a 3-D space of the captured scene, placing virtual cameras along a foreground trajectory in the 3-D space, and projecting 3-D background points on to the virtual cameras.