Offline Motion Description for Video Transcoding
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Solution Overview
Problem
The challenge lies in providing a seamless multimedia experience across diverse computing devices and networks with varying capabilities and bandwidths, as existing solutions require intensive computation and result in video content degradation during transcoding.
Innovation Solution
The offline motion description technique employs a hierarchical model for motion alignment, reducing processing complexity by compressing motion information based on correlations among neighboring macroblocks and partition modes, thus eliminating the need for costly motion estimation during transcoding.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple formats at multiple bit rates are created to accommodate different computing devices and bandwidths, then adaptability is improved, but computation complexity and storage space requirements increase significantly
Solution Approach 1:
The patent performs motion estimation and compression offline in advance, storing the results as motion descriptions. During online transcoding, these pre-computed motion descriptions are directly utilized without requiring re-estimation, thereby eliminating the need for intensive computation and storage of multiple formats while maintaining adaptability to different devices and bandwidths
Solution Approach 2:
The patent creates a compressed representation (motion description) that captures essential motion information from the original video. This compressed copy contains correlated motion data that can be reused across different transcoding scenarios, replacing the need to store and process multiple full-resolution format versions
2Productivity
If video content is compressed at high bit rate using conventional format with fast transcoding, then processing speed is improved, but video content quality degrades during transcoding
Solution Approach 1:
The patent performs comprehensive motion estimation offline before transcoding, capturing accurate motion information that would otherwise be lost in fast transcoding. This pre-computed motion description preserves video quality while enabling rapid online transcoding operations
Solution Approach 2:
The patent introduces motion description as an intermediary data structure that bridges the gap between source video and transcoded output. This intermediate representation preserves essential motion information, allowing high-quality transcoding at reduced bit rates without the degradation typical of conventional fast transcoding methods
3Manufacturing precision
If motion estimation is performed during transcoding to maintain video quality, then video quality is preserved, but computation complexity increases significantly
Solution Approach 1:
The patent performs motion estimation offline in advance and stores the results as motion descriptions. During online transcoding, these pre-computed motion descriptions are directly utilized without requiring re-estimation, thereby maintaining video quality while eliminating intensive computation during the transcoding process
Solution Approach 2:
The offline motion description serves the online transcoding process by providing ready-to-use motion information. The pre-computed motion descriptions automatically adapt to different transcoding scenarios without requiring additional computation, allowing the system to serve multiple transcoding needs from a single offline preparation
Data Source
AI summary
The present motion description technique provides a technique for defining a motion description offline. The motion description can then later be extracted from a multimedia representation and adapted to various multimedia-related applications in a manner that not only reduces the processing for motion estimation but also provides high compression performance during an encoding/transcoding process. The motion description technique employs a motion alignment scheme utilizing a hierarchical model to describe motion data of each macroblock in a coarse-to-fine manner. Motion information is obtained for motion vectors of macroblocks for different partition modes. The resulting motion information is compressed based on correlations among spatially neighboring macroblocks and among partition modes to form the offline motion description.