Visual object tracking performance measures revisited

The problem of visual tracking evaluation is sporting a large variety of performance measures, and largely suffers from lack of consensus about which measures should be used in experiments. This makes the cross-paper tracker comparison difficult. Furthermore, as some measures may be less effective than others, the tracking results may be skewed or biased towards particular tracking aspects. In this paper we revisit the popular performance measures and tracker performance visualizations and analyze them theoretically and experimentally. We show that several measures are equivalent from the point of information they provide for tracker comparison and, crucially, that some are more brittle than the others. Based on our analysis we narrow down the set of potential measures to only two complementary ones, describing accuracy and robustness, thus pushing towards homogenization of the tracker evaluation methodology. These two measures can be intuitively interpreted and visualized and have been employed by the recent Visual Object Tracking (VOT) challenges as the foundation for the evaluation methodology

Beyond standard benchmarks: Parameterizing performance evaluation in visual object tracking

Object-to-camera motion produces a variety of apparent motion patterns that significantly affect performance of short-term visual trackers. Despite being crucial for designing robust trackers, their influence is poorly explored in standard benchmarks due to weakly defined, biased and overlapping attribute annotations. In this paper we propose to go beyond pre-recorded benchmarks with post-hoc annotations by presenting an approach that utilizes omnidirectional videos to generate realistic, consistently annotated, short-term tracking scenarios with exactly parameterized motion patterns. We have created an evaluation system, constructed a fully annotated dataset of omnidirectional videos and the generators for typical motion patterns. We provide an in-depth analysis of major tracking paradigms which is complementary to the standard benchmarks and confirms the expressiveness of our evaluation approach

Analysis of Player Motion in Sport Matches

The system for analysis of player motion during sport matches, developed at University of Ljubljana will be presented. The system allows for non-intrusive measurement of positions of all players in indoor sports through whole match using only inexpensive video equipment - cameras mounted on the ceiling of the sports hall. Tracking process (obtaining trajectories from videos) is automatic and only supervised by operator, to initialize player positions at the beginning and correct the mistakes during the tracking. The software provides means for user friendly calibration of video data - using court markings of each supported sport (e.g. european handball, basketball, squash, tennis...) as reference coordinates. Manual annotations can be added, to complement the quantitative data. Software keeps synchronization between annotations and trajectory data and provides means to use custom annotation dictionaries. Due to calibration, the results are provided in court coordinates (meters, centimeters) and can be exported (synchronized with annotations in same file) for further analysis with any application (e.g. excel, SPSS). Software itself supports several kinds of graphical data presentations. If time allows, the software itself will be demonstrated with examples from different sports

Voronoi diagrams

In the thesis we first describe the definition of a Voronoi diagram and several properties of Voronoi diagrams in the plane. We also define triangulations of the plane and the concept of a Delaunay triangulation, and present the connection between Voronoi diagrams and Delaunay triangulations. We then present three different algorithms for constructing a Voronoi diagram in the plane, and provide a more detailed description of Fortune’s algorithm which is an example of a sweep line algorithm. Sweep line algorithms are especially widespread in computational geometry and are used for solving various problems in Euclidean space. We selected Fortune’s algorithm for constructing Voronoi diagrams, and implemented it in the Java programming language. The performance of our implementation of the algorithm was checked on several randomly generated datasets and on a dataset of geographic coordinates of public charging stations for electric cars in Slovenia

Voronoi diagrams

V diplomski nalogi najprej opišemo definicijo Voronoijevega diagrama in bolj podrobno lastnosti ravninskih Voronoijevih diagramov. Opišemo tudi triangulacijo ravnine, pojem Delaunayeve triangulacije in predstavimo povezavo med njima. Nato predstavimo tri različne algoritme za konstrukcijo ravninskih Voronoijevih diagramov in bolj podrobno pogledamo Fortunov algoritem, ki spada med algoritme s prebirno premico. Algoritmi s prebirno premico so posebej razširjeni v računski geometriji in z njimi rešujemo različne probleme v evklidskem prostoru. Za konstrukcijo Voronoijevega diagrama smo si izbrali Fortunov algoritem, ki smo ga implementirali v programskem jeziku Java. Pravilnost delovanja algoritma smo preverili na točkah, ki predstavljajo lokacije letališč v ZDA, lokacije javnih polnilnih mest za električne avtomobile v Sloveniji in na več naborih naključno generiranih točk.In the thesis we first describe the definition of a Voronoi diagram and several properties of Voronoi diagrams in the plane. We also define triangulations of the plane and the concept of a Delaunay triangulation, and present the connection between Voronoi diagrams and Delaunay triangulations. We then present three different algorithms for constructing a Voronoi diagram in the plane, and provide a more detailed description of Fortune’s algorithm which is an example of a sweep line algorithm. Sweep line algorithms are especially widespread in computational geometry and are used for solving various problems in Euclidean space. We selected Fortune’s algorithm for constructing Voronoi diagrams, and implemented it in the Java programming language. The performance of our implementation of the algorithm was checked on several randomly generated datasets and on a dataset of geographic coordinates of public charging stations for electric cars in Slovenia

Cheating Depth: Enhancing 3D Surface Anomaly Detection via Depth Simulation

RGB-based surface anomaly detection methods have advanced significantly. However, certain surface anomalies remain practically invisible in RGB alone, necessitating the incorporation of 3D information. Existing approaches that employ point-cloud backbones suffer from suboptimal representations and reduced applicability due to slow processing. Re-training RGB backbones, designed for faster dense input processing, on industrial depth datasets is hindered by the limited availability of sufficiently large datasets. We make several contributions to address these challenges. (i) We propose a novel Depth-Aware Discrete Autoencoder (DADA) architecture, that enables learning a general discrete latent space that jointly models RGB and 3D data for 3D surface anomaly detection. (ii) We tackle the lack of diverse industrial depth datasets by introducing a simulation process for learning informative depth features in the depth encoder. (iii) We propose a new surface anomaly detection method 3DSR, which outperforms all existing state-of-the-art on the challenging MVTec3D anomaly detection benchmark, both in terms of accuracy and processing speed. The experimental results validate the effectiveness and efficiency of our approach, highlighting the potential of utilizing depth information for improved surface anomaly detection.Comment: Accepted at WACV 202