Video Frame Error Recovery via Group of Pictures Position
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Solution Overview
Problem
Existing data storage devices face challenges in efficiently handling errors in video frames, particularly in surveillance systems or digital video recorders, where errors in critical frames can disrupt the decoding of subsequent frames.
Innovation Solution
A data storage device with a controller that retrieves video frames, detects errors, and selects a data recovery mechanism based on the frame's position within a group of pictures (GoP), using more robust mechanisms for frames closer to the beginning of the GoP and less robust mechanisms for frames closer to the end.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a robust data recovery mechanism is applied to all video frames, then error recovery capability is improved, but processing time and computational resources increase
Solution Approach 1:
The patent applies different data recovery mechanisms based on the local characteristics of video frames. I-frames, which are critical for video decoding, receive robust error correction code (ECC) based recovery, while P-frames and B-frames use simpler recovery methods. This localized approach ensures high reliability for critical frames without unnecessarily processing all frames with the same level of complexity.
Solution Approach 2:
The patent segments video frames into different types (I-frames, P-frames, B-frames) and applies different recovery strategies to each segment. This segmentation allows the system to focus computational resources on the most critical frames (I-frames) while using lighter processing for less critical frames, thereby reducing overall processing time while maintaining error recovery capability where it matters most.
2Measurement precision
If error correction code based recovery is used for all frames, then data accuracy is improved, but processing complexity increases
Solution Approach 1:
The patent implements local quality by applying ECC-based recovery only to I-frames where high data accuracy is critical for video decoding. For P-frames and B-frames, simpler recovery mechanisms are used, reducing processing complexity while maintaining sufficient accuracy for those frame types.
Solution Approach 2:
The patent segments frames by type and applies different recovery algorithms accordingly. This segmentation reduces overall processing complexity by avoiding the application of complex ECC-based recovery to all frames, while still ensuring high data accuracy for the most critical I-frames.
3Productivity
If exclusive-or based recovery is used for all frames, then processing speed is improved, but error recovery robustness decreases
Solution Approach 1:
The patent applies XOR-based recovery only to P-frames and B-frames where processing speed is prioritized and the impact of errors is less critical. For I-frames, robust ECC-based recovery is used instead, ensuring high error recovery robustness where it is most needed for video decoding integrity.
Solution Approach 2:
The patent segments frames by type and applies different recovery mechanisms: ECC for I-frames and XOR for P/B frames. This segmentation achieves a balance between processing speed and error recovery robustness by matching the recovery method to the criticality of each frame type.
Data Source
AI summary
A data storage device and method are provided for selecting a data recovery mechanism based on a video frame position. In one embodiment, a data storage device is provided comprising a memory and a controller. The controller is configured to retrieve a video frame stored in the memory; detect an error in the video frame; and select how to handle the error based on a position of the video frame in a group of pictures. Other embodiments are provided.