Drone-Person Tracking in Uniform Appearance Crowd: A New Dataset.

ABSTRACT: 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 121 K frames, each manually annotated with bounding boxes and attributes. During dataset creation, we carefully consider 18 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,

SUBMITTER: Alansari M 

PROVIDER: S-EPMC10762134 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature