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This paper presents a novel hierarchical spatiotemporal orientation representation for spacetime image analysis. It is designed to combine the benefits of the multilayer architecture of ConvNets and… (More)
In this paper, we present a novel 3D descriptor that bridges the gap between global and local approaches. While local descriptors proved to be a more attractive choice for object recognition within… (More)
This document will review the most prominent proposals using multilayer convolutional architectures. Importantly, the various components of a typical convolutional network will be discussed through a… (More)
Nowadays 3D images are becoming a widely used tool in many computer vision tasks, such as scene segmentation or object recognition. A common problem when using 3D images, is that often the size of… (More)
In this paper, we implement and compare three different clustering algorithms for the purpose of 3D image segmentation. Specifically, the K-means, Mean Shift, and Hierarchical methods are studied,… (More)
We introduce a new large scale dynamic texture dataset. With over 10,000 videos, our Dynamic Texture DataBase (DTDB) is two orders of magnitude larger than any previously available dynamic texture… (More)