Shot Sequence Clustering for Adaptive Media Encoding
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Solution Overview
Problem
Existing media streaming technologies face inefficiencies in encoding media titles due to the use of monolithic encoding techniques, which result in unnecessary computational and storage resource usage and increased bandwidth requirements, as they do not account for varying content complexity across a media title.
Innovation Solution
The proposed method involves partitioning shot sequences into clusters based on features and using optimized encoding points specific to each cluster, allowing for efficient encoding by reducing the number of encoding points needed and optimizing resource usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If monolithic encoding techniques are used to encode media titles, then encoding simplicity is maintained, but computational resources and storage resources are wasted due to uniform encoding of varying content complexity
Solution Approach 1:
The media title is divided into multiple shot sequences based on temporal boundaries, and each shot sequence is further classified into different complexity clusters. This segmentation allows different encoding parameters to be applied to different segments, avoiding the waste of encoding simple portions with high-bitrate parameters intended for complex portions.
Solution Approach 2:
Different encoding parameter sets (quality levels) are assigned to different clusters of shot sequences based on their complexity characteristics. Complex shot sequences receive higher quality encoding parameters while simple shot sequences receive lower quality parameters, ensuring that computational resources are allocated according to actual content needs rather than uniformly across the entire media title.
2Ease of manufacture
If monolithic encoding techniques are used with uniform resolution and encoding parameters, then encoding process is simplified, but bandwidth requirements increase due to inefficient resource usage
Solution Approach 1:
The media title is segmented into shot sequences that are clustered by complexity, enabling differentiated encoding strategies for different segments. This reduces the total bitrate required compared to uniform encoding, as simple segments are encoded at lower bitrates while only complex segments receive higher bitrates.
Solution Approach 2:
Encoding parameters including resolution and bitrate are localized to match the complexity of each shot sequence cluster. This ensures that bandwidth is consumed efficiently by allocating higher quality encoding only where visually necessary, rather than wasting bandwidth on simple portions that would look identical at lower quality.
3Stability of the object's composition
If the same encoding parameters are applied throughout the media title, then encoding consistency is maintained, but visual quality efficiency decreases for simple portions that achieve target quality at lower bitrates
Solution Approach 1:
The media title is divided into shot sequences with consistent temporal boundaries, and these segments are grouped into clusters maintaining internal consistency. This segmentation approach preserves a form of consistency (within clusters) while enabling quality optimization across different cluster types.
Solution Approach 2:
Encoding parameters are adjusted locally for each cluster type to achieve the target visual quality most efficiently. Simple clusters use lower bitrate parameters while complex clusters use higher bitrate parameters, both achieving their respective target qualities without waste. This localized parameter adjustment maintains quality efficiency while preserving consistency within each cluster category.
Data Source
AI summary
In various embodiments, a sequence-based encoding application partitions a set of shot sequences associated with a media title into multiple clusters based on at least one feature that characterizes media content and/or encoded media content associated with the media title. The clusters include at least a first cluster and a second cluster. The sequence-based encoding application encodes a first shot sequence using a first operating point to generate a first encoded shot sequence. The first shot sequence and the first operating point are associated with the first cluster. By contrast, the sequence-based encoding application encodes a second shot sequence using a second operating point to generate a second encoded shot sequence. The second shot sequence and the second operating point are associated with the second cluster. Subsequently, the sequence-based encoding application generates an encoded media sequence based on the first encoded shot sequence and the second encoded shot sequence.