Drone-Person Tracking in Uniform Appearance Crowd (D-PTUAC)

Drone-person tracking in uniform appearance crowds poses unique challenges due to the difficulty in distinguishing individuals with similar attire and multi-scale variations. To address this issue and facilitate the development of effective tracking algorithms, we present a novel dataset named D-PTUAC (Drone-Person Tracking in Uniform Appearance Crowd). The dataset comprises 138 sequences comprising over 121K frames, each manually annotated with bounding boxes and attributes. During dataset creation, we carefully consider 17 challenging attributes encompassing a wide range of viewpoints and scene complexities. These attributes are annotated to facilitate the analysis of performance based on specific attributes. Extensive experiments are conducted using 44 state-of-the-art (SOTA) trackers, and the performance gap demonstrate the need for a dedicated end-to-end aerial visual object tracker that accounts the inherent properties of aerial environment.<br>

搜集汇总

背景与挑战

背景概述

D-PTUAC是一个专门针对无人机视角下人群跟踪的数据集，特别关注着装相似人群的挑战性场景。数据集包含138个序列和超过121K帧，每帧都手动标注边界框和17个属性，如多尺度变化和复杂场景，旨在支持跟踪算法的开发和性能分析。实验使用44种最先进的跟踪器，突显了在无人机环境中开发专用跟踪器的需求。