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With emerging demand for large-scale video analysis, MPEG initiated the compact descriptor for video analysis (CDVA) standardization in 2014. Beyond handcrafted descriptors adopted by the current MPEG-CDVA reference model, we study the problem of deep learned global descriptors for video matching, localization, and retrieval. First, inspired by a recent invariance theory, we propose a nested invariance...
Automatically detecting violence in videos is paramount for enforcing the law and providing the society with better policies for safer public places. In addition, it may be essential for protecting minors from accessing inappropriate contents on-line, and for helping parents choose suitable movie titles for their children. However, this is an open problem as the very definition of violence is subjective...
This paper presents a novel automatic quantitative measurement method for assessment of the performance of image registration algorithms designed for registering retina fundus images. To achieve automatic quantitative measurement, we propose the use of edges and edge dissimilarity measure for determining the performance of retina image registration algorithms. Our input is the registered pair of retina...
We propose a novel monocular visual inertial odometry algorithm that combines the advantages of EKF-based approaches with those of direct photometric error minimization methods. The method is based on sparse, very small patches and incorporates the minimization of photometric error directly into the EKF measurement model so that inertial data and vision-based surface measurements are used simultaneously...
The goal of image authentication is to accept content-preserving operations and reject content-altering manipulations. So,it is increasingly approached by extracting content-based invariant features from original images and verifying their preservation in received images at later times. Since sparsity usually implies invariance, sparse feature representation has drawn significant attention from the...
Intuitive and easily interpretable performance measures, repeatability and matching performance, for local feature detectors and descriptors were introduced by Mikolajczyk et al. [10, 9]. They, however, measured performance in a wide baseline setting that does not correspond to the visual object categorisation problem which is a popular application of the detectors and descriptors. The limitation...
We review some recent techniques for 3D tracking and occlusion handling for computer vision-based augmented reality. We discuss what their limits for real applications are, and why object recognition techniques are certainly the key to further improvements.
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