Scalable Video ROI Mapping via Slice Group Segmentation
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Solution Overview
Problem
Existing scalable video coding (SVC) methods do not effectively support multiple regions of interest (ROIs) and lack efficient mechanisms for independent decoding with scalability, particularly in heterogeneous environments where limited terminals and networks require selective video streaming.
Innovation Solution
A method is introduced that sets and allocates ROI identification numbers and slice group identification numbers, generating messages with associated information for scalable video bitstreams, allowing for selective extraction and decoding of specific ROIs with desired scalability, even in cases of overlapped regions, using flexible macroblock ordering (FMO) and supplemental enhancement information (SEI) messages.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple ROIs are defined with arbitrary forms in SVC, then the adaptability to different terminal requirements is improved, but the device complexity increases due to the need for mapping ROI identification numbers to slice group identification numbers
Solution Approach 1:
The video frame is divided into multiple slice groups, each corresponding to a specific ROI. By segmenting the frame into manageable regions with unique slice group IDs, the system can independently encode and decode each ROI, enabling adaptability to different terminal requirements while maintaining manageable complexity through structured organization
Solution Approach 2:
A mapping mechanism is introduced as an intermediary between ROI identification numbers and slice group identification numbers. This mapping table serves as a mediator that translates between the logical ROI representation and the physical slice group structure, allowing flexible ROI definition without directly complicating the encoding/decoding process
2Productivity
If independent decoding of specific ROIs is enabled, then the productivity of video streaming is improved by allowing selective decoding, but the device complexity increases due to the need for independent segment decoding mechanisms
Solution Approach 1:
The video stream is segmented into independent slice groups corresponding to different ROIs, each with its own identification number. This segmentation allows receivers to independently decode only the slice groups containing their required ROIs, improving streaming efficiency by avoiding unnecessary decoding of irrelevant regions while maintaining manageable complexity through the use of standard decoding processes applied to each segment
Solution Approach 2:
The system enables partial decoding by allowing receivers to decode only the specific slice groups containing their required ROIs rather than decoding the entire frame. This partial action approach improves productivity by reducing unnecessary processing while the complexity is managed by using the same decoding mechanisms as full-frame decoding, just applied selectively to subsets of data
3Ease of manufacture
If ROIs are coded into rectangular regions defined by VOP, then the ease of manufacture is improved by simplifying the coding process, but the manufacturing precision deteriorates by losing the arbitrary form of object regions
Solution Approach 1:
The video frame is divided into multiple rectangular slice groups, each corresponding to a specific ROI. By segmenting the frame into manageable regions with unique slice group IDs, the system can independently encode and decode each ROI, enabling adaptability to different terminal requirements while maintaining manageable complexity through structured organization
Solution Approach 2:
Different slice groups (rectangular regions) are assigned different properties based on their corresponding ROI requirements. Each slice group can have independent encoding parameters, quality settings, and identification numbers, allowing the system to maintain simple rectangular coding structures while achieving precise representation of arbitrary ROI shapes through selective activation and mapping of specific slice groups
Data Source
AI summary
A multiple ROI (region of interest) setting method and apparatus in scalable video coding and an ROI reconstructing method and apparatus are provided. The multiple ROI setting apparatus includes: an ROI setting unit which sets at least one or more ROIs and allocates ROI identification numbers to the each of ROIs; a mapping unit which allocates at least one or more slice group identification numbers to the at least one or more ROI identification numbers; and a message generating unit which generates a message including ROI-associated information, slice-group-associated information, mapping information on mapping of the ROI identification number to the at least one or more slice group identification numbers, and scalability information.