Dynamic Object Detection via Camera Motion State Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing dynamic object detection methods for videos captured by dynamic cameras face challenges in accurately estimating camera motion, leading to incorrect object detection and failure in dynamic environments, especially when the background-oriented approach is used.
Innovation Solution
A system and method that analyze local and global motions to determine the camera's motion state, flexibly update the background model based on this state, and detect dynamic objects using a processor with dedicated engines for video extraction, motion estimation, camera state determination, background model updating, and object detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a background-oriented approach is used for dynamic object detection in videos captured by a dynamic camera, then the system can operate without assumptions about object positioning, but the detection accuracy deteriorates due to inaccurate camera motion estimation
Solution Approach 1:
The patent segments the motion estimation problem into two distinct components: local motion estimation (object motion relative to camera) and global motion estimation (camera motion). By separating these motions and processing them through different engines with specialized algorithms, the system achieves accurate camera motion estimation while maintaining adaptability to various video environments without requiring assumptions about object positioning.
2Reliability
If a module is added to estimate camera motion in the background-oriented approach, then detection performance improves, but the system complexity increases
Solution Approach 1:
The patent merges the local motion estimation engine and global motion estimation engine into a unified processing pipeline that works协同 to achieve accurate camera motion estimation. This integrated approach improves detection reliability while avoiding the complexity of completely separate systems, as the two engines share data and coordinates efficiently within the same architectural framework.
3Measurement precision
If camera motion is inaccurately estimated, then the background model becomes unreliable, but adding motion estimation modules increases computational overhead
Solution Approach 1:
The patent performs preliminary camera motion estimation using the global motion estimation engine before updating the background model. By pre-calculating the projection matrix and camera motion state, the system ensures accurate background model updates while optimizing computational resource usage through efficient coordinate transformations and motion compensation techniques that reduce redundant calculations.
Data Source
AI summary
Provided is a dynamic object detecting technique, and more specifically, a system and method for determining a state of a motion of a camera on the basis of a local motion estimated on the basis of a video captured by a dynamic camera and a result of analyzing a global motion, flexibly updating a background model according to the state of the motion of the camera, and flexibly detecting a dynamic object according to the state of the motion of the camera.