Temporal Change Detection using Optical Flow and Mask R-CNN: A Comprehensive Approach
Temporal change detection is a crucial task in computer vision, where the goal is to identify areas of change between two or more images in a sequence. In this post, we'll explore a powerful approach that combines optical flow and Mask R-CNN to achieve state-of-the-art results.
What is Optical Flow?
Optical flow is a technique used to estimate the motion of pixels between two consecutive frames in an image sequence. It's a fundamental concept in computer vision and has numerous applications, including video stabilization, object tracking, and motion estimation.
What is Mask R-CNN?
Mask R-CNN is a popular deep learning-based object detection algorithm that has achieved remarkable results in various tasks, including image classification, object detection, and segmentation. It's a powerful tool for identifying and segmenting objects in images.
*Combining Optical Flow and Mask R-CNN...
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