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Real-time CNN-based Segmentation Architecture for Ball Detection in a Single View Setup

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Document pages: 8 pages

Abstract: This paper considers the task of detecting the ball from a single viewpointin the challenging but common case where the ball interacts frequently withplayers while being poorly contrasted with respect to the background. Wepropose a novel approach by formulating the problem as a segmentation tasksolved by an efficient CNN architecture. To take advantage of the balldynamics, the network is fed with a pair of consecutive images. Our inferencemodel can run in real time without the delay induced by a temporal analysis. Wealso show that test-time data augmentation allows for a significant increasethe detection accuracy. As an additional contribution, we publicly release thedataset on which this work is based.

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