DSEC-MOT: an Event-based MOT Dataset

Introduction Welcome to the new challenging event-based multi-object tracking dataset (DSEC-MOT) repository. Our goal is to provide a challenging and diverse event-based MOT dataset with various real-world scenarios to facilitate the objective and comphrehensive evaluation of event-based multi-object tracking algorithms. This dataset, built upon DSEC(https://dsec.ifi.uzh.ch/), contains a variety of traffic entities and complex scenarios, aiming to address the current lack of event-based MOT datasets. Dataset Statistics DSEC-MOT contains: - 12 annotated sequences with a total of 37,080 boxes, 502 tracks, and 769.2-second duration - 7 object classes including cars, pedestrians, bicycles, motorcycles, buses, trucks, and trains - Challenging scenarios including crowded urban areas and rural scenes with various lighting conditions - Severe occlusions, making the dataset suitable for testing trackers' occlusion handling capabilities - Event resolution 640 x 480引言 欢迎使用全新的高挑战性基于事件的多目标跟踪（event-based multi-object tracking）数据集仓库DSEC-MOT。本数据集旨在提供一个兼具挑战性与多样性的基于事件的多目标跟踪数据集，涵盖各类真实世界场景，以助力对基于事件的多目标跟踪算法开展客观且全面的评估。本数据集依托DSEC（https://dsec.ifi.uzh.ch/）构建，包含多种交通实体与复杂场景，旨在弥补当前基于事件的多目标跟踪数据集匮乏的现状。 数据集统计信息 DSEC-MOT包含以下内容： - 12条带标注序列，总计37080个标注框、502条跟踪轨迹，总时长769.2秒 - 7类目标类别，涵盖汽车、行人、自行车、摩托车、公共汽车、卡车及火车 - 包含高挑战性场景，如拥挤城区与不同光照条件下的乡村路段 - 存在严重遮挡情况，可用于测试跟踪器的遮挡处理能力 - 事件分辨率为640×480

搜集汇总

背景与挑战

背景概述

DSEC-MOT是一个基于事件的多目标跟踪数据集，包含12个标注序列和7种交通实体类别，旨在为算法评估提供多样化和挑战性的真实场景。数据集特点包括高分辨率事件数据（640x480）和复杂场景下的严重遮挡情况，适用于测试跟踪器的遮挡处理能力。