Skeleton Detection Using Motion Vectors and IMB Ratios
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Solution Overview
Problem
Current skeleton detection methods, such as Openpose and AlphaPose, face inefficiencies due to high calculation loads and are not optimized for varying lighting conditions and complex backgrounds, making them less effective in real-time applications.
Innovation Solution
A method and device that utilize motion vectors to estimate skeleton information in video frames, determining the use of motion vectors based on intra-coded macroblock ratios to reduce the reliance on computationally intensive skeleton detection algorithms, thereby improving processing efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If skeleton detection algorithms such as Openpose or AlphaPose are used, then skeleton information can be extracted from images, but the calculation load is high and calculation efficiency is low
Solution Approach 1:
The patent applies preliminary action by performing motion estimation and generating motion vectors before skeleton detection. The motion vectors are pre-calculated from reference frames and used to initialize skeleton node positions, reducing the search space for subsequent detection algorithms and lowering computational requirements
Solution Approach 2:
The patent uses motion vectors as temporary, low-cost auxiliary information to guide skeleton detection. These motion vectors are easily computed from video compression data and discarded after use, replacing the need for heavy computational resources in traditional skeleton detection
2Measurement precision
If traditional skeleton detection methods are used, then skeleton information can be obtained, but the processing time is long and real-time detection is difficult
Solution Approach 1:
Motion vectors are pre-computed during video encoding, providing ready-to-use displacement information before skeleton detection begins. This preliminary preparation significantly reduces the time required for real-time skeleton detection while maintaining accuracy
Solution Approach 2:
Motion vectors serve as an intermediary that bridges video frames and skeleton detection. Instead of directly analyzing complex image data, the system uses motion vectors as a simplified intermediate representation to guide skeleton node positioning, reducing processing time
Data Source
AI summary
A method for detecting a human skeleton is provided. The method includes: receiving a video frame, wherein the video frame comprises a human body; determining whether the video frame comprises prediction information; determining whether a first intra-coded macroblock (IMB) ratio of a target area comprising the human body in the video frame is greater than a first threshold when the video frame comprises the prediction information; and using a motion vector (MV) to estimate skeleton information of the human body when the first IMB ratio of the target area is not greater than the first threshold.