Consistency measure for image segmentation processes

This invention describes a system that checks how consistently an object is outlined (segmented) across different frames of a video. It works by identifying key characteristics of the segmented object in one frame and comparing them to the same object's characteristics in another frame. It also compares visual features from the original images in those same areas to determine if the segmentation is stable over time. The claims describe this as a software system running on a processor.

Why it matters: Since 2021, significant advancements in deep learning architectures for computer vision, particularly in real-time image segmentation and robust feature extraction, have made implementing such consistency checks more efficient and accurate. Newer models can provide more reliable segmentation masks and features, improving the foundation for this temporal consistency measurement.

Status: Not in forceListed as no longer active. The specific reason is not in the record we hold.
How hard to build: SpecializedSoftware logic, advanced image processing, machine learning

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