Object-based Video compression using neural networks
This paper presents a new object-based video compression
approach. It consists on predicting video objects motions
throughout the scene. Neural networks are used to carry out the
prediction step. A multi-step- ahead prediction is performed to
predict the video objects trajectories over the sequence. In order
to reduce video data, only the background of the video sequence
is transmitted with the different detected video objects as well as
their initial properties such as placement and dimensions.
Experimental results show the effectiveness of the proposed
approach in terms of the compression rates.
Keywords: video compression, object tracking, neural network, multi-step-ahead prediction
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