A Novel and Effective Short Track Speed Skating Tracking System

This dissertation proposes a novel and effective system for tracking high-speed skaters. A novel registration method is employed to automatically discover key frames to build the panorama. Then, the homography between a frame and the real world rink can be generated accordingly. Aimed at several challenging tracking problems of short track skating, a novel multiple-objects tracking approach is proposed which includes: Gaussian mixture models (GMMs), evolving templates, constrained dynamical model, fuzzy model, multiple templates initialization, and evolution. The outputs of the system include spatialtemporal trajectories, velocity analysis, and 2D reconstruction animations. The tracking accuracy is about 10 cm (2 pixels). Such information is invaluable for sports experts. Experimental results demonstrate the effectiveness and robustness of the proposed system

MonoTrack: Shuttle trajectory reconstruction from monocular badminton video

Trajectory estimation is a fundamental component of racket sport analytics, as the trajectory contains information not only about the winning and losing of each point, but also how it was won or lost. In sports such as badminton, players benefit from knowing the full 3D trajectory, as the height of shuttlecock or ball provides valuable tactical information. Unfortunately, 3D reconstruction is a notoriously hard problem, and standard trajectory estimators can only track 2D pixel coordinates. In this work, we present the first complete end-to-end system for the extraction and segmentation of 3D shuttle trajectories from monocular badminton videos. Our system integrates badminton domain knowledge such as court dimension, shot placement, physical laws of motion, along with vision-based features such as player poses and shuttle tracking. We find that significant engineering efforts and model improvements are needed to make the overall system robust, and as a by-product of our work, improve state-of-the-art results on court recognition, 2D trajectory estimation, and hit recognition.Comment: To appear in CVSports@CVPR 202

Measuring Bridge Construction Efficiency Using the Wireless Real-Time Video Monitoring System

To enhance the efficiency of bridge construction, the wireless real-time video monitoring system (WRITE) was developed. Utilizing the advanced technologies of computer vision and artificial neural networks, the developed system first wirelessly acquired a sequence of images of work face operations. Then human pose analyzing algorithms processed these images in real time to generate human poses associated with construction workers who performed the operations. Next, a portion of the human poses were manually classified into three categories as effective work, contributory work, and ineffective work and were used to train the built-in artificial neural networks (ANN). Finally, the trained neural networks were employed to decide the ongoing laborers’ working status by comparing the in coming images to the developed human poses. The developed system was tested for accuracy on a bridge construction project. Results of the test showed that efficiency measurements by the system were reasonably accurate when compared to the measurements produced by the manual method. Thus, the success of this research indicates promise for enabling project managers to quickly identify work-face operation problems and to take actions immediately to address these problems

Creating walk-through images from a video sequence of a dynamic scene

A comprehensive scheme for creating walk-through images from a video sequence by generalizing the idea of tour into the picture (TIP) was discussed. The proposed scheme was designed to incorporate a new modeling scheme on a vanishing circle identified in the video and an automatic background detection from the video. This scheme let users experience the feel of navigating into a video sequence with their own interpretation and imagination about a given scene. The proposed scheme covers several types of video films of dynamic scenes such as sports coverage, cartoon animation and movie films in which object continuously change shapes and locations

Workshop on Particle Capture, Recovery and Velocity/Trajectory Measurement Technologies

A workshop on particle capture, recovery, and velocity/trajectory measurement technologies was held. The primary areas covered were: (1) parent-daughter orbit divergence; (2) trajectory sensing; (3) capture medium development: laboratory experiments, and (4) future flight opportunities

The Missouri Miner, August 27, 1981

https://scholarsmine.mst.edu/missouri_miner/3282/thumbnail.jp

Rastreo de jugadores de fútbol mediante grafos multipartitos utilizando videos de ultra alta definición

Este trabajo describe un algoritmo de rastreo para jugadores de fútbol basado en gráficos multipartitos diseñados para el procesamiento de un gran volumen de datos. El algoritmo propuesto utiliza varias características como: contornos, información cromática y dinámica, para la asociación de datos dentro de un gráfico multipartito para resolver oclusiones y rastrear a jugadores de fútbol. La implementación paralela del algoritmo realiza un esquema consumidor-productor para superponer el tiempo de procesamiento de los dos procedimientos principales del algoritmo: segmentación y rastreo; así como un patrón de comunicación de envío y recepción para propagar las identidades de objetos. Mostramos cómo un sistema híbrido de paralelización de datos y tareas mejora el tiempo de ejecución para videos 4K, logrando una aceleración igual a 19.24 y una velocidad de procesamiento de 21.71 FPS con 128 subprocesos. Utilizando la base de datos ISSIA se obtuvieron valores similares de las métricas de FP y FN con una velocidad de rastreo superior.This work describes a tracking algorithm for football players based on multipartite graphs designed for the processing of high volume of data. The proposed algorithm use several characteristics such as: contours, chromatic and dinamic information, for the association of data within a multipartite graph to solve oclusions and track football player. The parallel implementation of the algorithm performce a consumer-producer scheme to overlap the computing time of the two main procedures of the tracking algorithm: segmentation and tracking; as well a send-and-receive communication pattern to propagate the blob identities. We show how an hybrid system of data and task parallelization improves the execution time for 4K videos, achieving a speedup equal to 19.24 and a processing speed of 21.71 FPS with 128 threads. Using the ISSIA database, similar values were obtained from the FP and FN metrics with a higher tracking rate.UCR::Vicerrectoría de Investigación::Sistema de Estudios de Posgrado::Ingeniería::Maestría Académica en Ingeniería Eléctric