Multiple Bit Rate Video Encoding With ROI Bit Allocation
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Solution Overview
Problem
Existing video streaming methods face challenges in optimizing user experience over variable bandwidth networks, leading to inconsistent video quality and inefficient use of processing power and storage due to constant bit rate encoding or multiple bit rate encoding with inadequate consideration of user preferences.
Innovation Solution
A multiple bit rate video encoder that analyzes user preferences and network conditions to allocate bits differently within frames, prioritizing segments of interest over non-interesting segments, ensuring high-quality display of important content even during bandwidth fluctuations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If video content is encoded at multiple bit rates and stored in separate buffers, then the client can request appropriate quality based on available bandwidth, but this requires significant processing power for transcoding and additional storage space at the server
Solution Approach 1:
The system performs preliminary analysis of video frames to identify regions of interest before encoding, using metadata such as scene type, object detection, and user preference data to pre-determine which segments require higher quality encoding. This preliminary classification enables efficient bit allocation during the encoding process without requiring multiple full transcodings.
Solution Approach 2:
The patent applies different quality levels to different portions of the same video frame based on user interest. Regions identified as containing objects of interest (e.g., favorite athletes, key actions) are encoded at higher bit rates, while less important regions use lower bit rates. This selective quality approach maintains overall video quality where needed while reducing total bandwidth consumption.
2Ease of manufacture
If video content is encoded at constant bit rate based on minimum available bandwidth, then the server can simplify encoding processes, but the user experiences reduced video quality when network conditions are good
Solution Approach 1:
The system dynamically adjusts the bit rate allocation for different video segments based on real-time network conditions and pre-analyzed user interest data. When bandwidth is available, higher bit rates are allocated to regions of interest; when bandwidth is limited, the system prioritizes maintaining quality in critical regions while reducing quality in less important areas. This dynamic adaptation resolves the contradiction between encoding simplicity and quality consistency.
3Device complexity
If the entire frame is encoded at the same bit rate, then the encoding process is simplified, but too many bits are allocated to segments the user is not interested in and too few bits to segments the user is interested in
Solution Approach 1:
The video frame is divided into multiple segments or regions based on detected objects and user interest profiles. Each segment is independently encoded with bit rate allocation proportional to its importance to the user. For example, if a user is interested in a particular athlete, segments containing that athlete receive higher bit rates, while segments showing less relevant areas use lower bit rates. This segmentation enables differentiated quality without requiring complex manual encoding processes.
Data Source
AI summary
Systems and methods for encoding a video stream at multiple bit rates is disclosed herein. An encoder divides each frame of a video stream into a plurality of portions and allocates an available number of bits between the plurality of portions based on user preference information. Portions having one or more objects of interest to the viewer determined based on the user preference information are allocated a higher number of available bits while portions of the frames that do not include one or more objects of interest are allocated a minimum number of bits from the available bits.