Video Tile-Level Encoding for Viewport-Focused 360° Decoding
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Solution Overview
Problem
The increasing size, resolution, and frame rate of video data necessitate improved encoding and decoding techniques to manage the growing amount of data efficiently, as existing compression methods like H.264/AVC and HEVC are becoming insufficient.
Innovation Solution
The method involves setting levels or tiers for specific regions within a video, splitting pictures into tiles, and configuring network abstraction layers to allow for optimized encoding and decoding, enabling parallel processing and selective decoding based on region-specific qualities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If video data is compressed using existing techniques like H.264/AVC or HEVC, then data storage and transmission are improved, but encoding and decoding efficiency becomes insufficient for increasing video size, resolution, and frame rate
Solution Approach 1:
The video picture is divided into multiple tiles, and each tile is further divided into tile groups. This segmentation allows parallel processing of different regions, improving encoding and decoding efficiency for high-resolution and high-frame-rate video data without requiring processing of the entire frame sequentially.
Solution Approach 2:
Different quality levels are applied to different regions of the video picture. The viewport region (important area) is encoded with higher quality, while non-viewport regions use lower quality. This is achieved through region-specific quantization parameters and selective decoding, improving overall efficiency by allocating resources according to regional importance.
2Speed
If selective decoding is implemented for viewport regions, then decoding speed is improved, but region identification and processing complexity increases
Solution Approach 1:
Viewport region information is pre-defined and signaled in the video bitstream before decoding occurs. The encoder provides advance notice of which regions are viewport regions through syntax elements in the tile group header, allowing the decoder to prepare for selective decoding without complex real-time analysis during the decoding process.
Solution Approach 2:
The decoding process is designed to automatically handle region identification through predefined syntax elements and flags in the bitstream. The decoder uses the viewport region information already embedded in the data structure, eliminating the need for external region identification systems or complex post-processing algorithms.
3Productivity
If parallel processing is enabled through picture splitting, then encoding and decoding speed is improved, but hardware resource requirements increase
Solution Approach 1:
The picture is divided into multiple independent tiles and tile groups that can be processed in parallel. Each tile group contains self-contained data structures and syntax elements, allowing different hardware units to process multiple regions simultaneously without requiring excessive inter-communication or shared resources, thus improving speed with moderate hardware increases.
Data Source
AI summary
Disclosed is a method and apparatus for encoding/decoding a video. According to an embodiment, provided is a method of setting a level for each of one or more regions, including decoding a definition syntax element related to level definition and a designation syntax element related to target designation from a bitstream; defining one or more levels based on the definition syntax element; and setting a target level designated by the designation syntax element among the defined levels for a target region designated by the designation syntax element.