Latent-Space Video Transitions for Seamless Stream Switching
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Solution Overview
Problem
Existing video-streaming platforms face challenges in providing seamless transitions between diverse videos, leading to visual discontinuity and abrupt changes that negatively affect the user experience.
Innovation Solution
A system and method using generative adversarial networks (GANs) to generate smooth video transitions by identifying key images in source and target videos, embedding them in a latent vector space, and interpolating between these embeddings to create a seamless transition sequence.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If videos are played back-to-back with immediate transitions, then video streaming efficiency is improved, but visual discontinuity and abrupt changes occur that negatively affect user experience
Solution Approach 1:
The patent introduces an intermediary transition video sequence that mediates between the first video and second video. This transition sequence is generated by extracting end frames from both videos, embedding them in latent space, interpolating between embeddings, and decoding intermediate embeddings to create smooth visual transitions that eliminate abrupt changes while maintaining streaming efficiency
Solution Approach 2:
The system performs preliminary actions by pre-processing video frames to extract key end frames and pre-computing their embeddings in latent space. This preparation enables rapid generation of transition sequences during video playback without compromising streaming efficiency, as the heavy computational work is done in advance
2Adaptability or versatility
If diverse videos are selected from different categories, then user viewing diversity is improved, but transition smoothness deteriorates due to lack of visual coherence
Solution Approach 1:
The patent transforms the transition problem from pixel-space manipulation to latent-space interpolation. By embedding video frames in a high-dimensional latent vector space and performing linear interpolation in this abstract dimension, the system can smoothly transition between visually diverse content while maintaining coherence, then map the interpolated latent vectors back to realistic video frames through the generator network
Data Source
AI summary
A method for generating a video transition sequence between a first and a second video is provided. The method first identifies and embeds starting and ending images for the video transition sequence into a latent vector space. The method then interpolates to generate an interpolation trajectory between the starting and ending image embeddings within the latent vector space. The method then reconstructs the interpolation trajectory from the latent vector space to a final video transition sequence in the original image vector space. This video transition sequence is then displayed so as to smoothly transition between two videos.


