Encord Computer Vision Glossary
Ghost frames, also known as phantom frames or interpolated frames, are artificial frames that are inserted into a video sequence in order to increase the frame rate and make the motion appear smoother. This is typically done in order to meet the requirements of certain display devices or to match the frame rate of another video.
In computer vision, ghost frames are created by using algorithms that analyze the motion of objects within a video and predict the movement of those objects between actual frames. This prediction is used to generate a new frame that appears as if it was captured at the same time as the surrounding frames.
How do you produce ghost frames for computer vision?
There are several techniques for producing ghost frames, such as linear interpolation, which estimates the motion of objects between frames using a straightforward mathematical formula, and more sophisticated techniques like optical flow, which makes more precise predictions using knowledge of the motion and shape of the objects.
Increased frame rates for smoother motion, the ability to match the frame rate of another video, and the capacity to upconvert lower resolution or lower frame rate video to a higher resolution or frame rate are just a few advantages of using ghost frames in computer vision applications.
The use of ghost frames may, however, have certain downsides, such as the potential to introduce glitches or distortions into the video and the increased computing burden of producing the extra frames. Furthermore, if the ghost frames are incorrectly generated, the video's quality or realism may suffer noticeably.
Overall, ghost frames can be an effective technique in computer vision for boosting frame rate and motion smoothness in a video, but it's crucial to carefully weigh the potential trade-offs and restrictions of this method.
Discuss this blog on Slack
Join the Encord Developers community to discuss the latest in computer vision, machine learning, and data-centric AIJoin the community