Drones, or general UAVs, equipped with cameras have been fast deployed with a wide range of applications, including agriculture, aerial photography, and surveillance …
A Gaidon, Q Wang, Y Cabon, E Vig - Proceedings of the IEEE …, 2016 - cv-foundation.org
Modern computer vision algorithms typically require expensive data acquisition and accurate manual labeling. In this work, we instead leverage the recent progress in computer …
This paper revisits the classical multiple hypotheses tracking (MHT) algorithm in a tracking- by-detection framework. The success of MHT largely depends on the ability to maintain a …
This paper introduces a novel approach to the task of data association within the context of pedestrian tracking, by introducing a two-stage learning scheme to match pairs of …
J Son, M Baek, M Cho, B Han - Proceedings of the IEEE …, 2017 - openaccess.thecvf.com
Abstract We propose Quadruplet Convolutional Neural Networks (Quad-CNN) for multi- object tracking, which learn to associate object detections across frames using quadruplet …
SH Bae, KJ Yoon - IEEE transactions on pattern analysis and …, 2017 - ieeexplore.ieee.org
Online multi-object tracking aims at estimating the tracks of multiple objects instantly with each incoming frame and the information provided up to the moment. It still remains a …
Data association problems are an important component of many computer vision applications, with multi-object tracking being one of the most prominent examples. A typical …
Data association is a key step within the multi-object tracking pipeline that is notoriously challenging due to its combinatorial nature. A popular and general way to formulate data …
D Frossard, R Urtasun - 2018 IEEE international conference on …, 2018 - ieeexplore.ieee.org
In this paper we propose a novel approach to tracking by detection that can exploit both cameras as well as LIDAR data to produce very accurate 3D trajectories. Towards this goal …