Hierarchical Instance Tracking to Balance Privacy Preservation with Accessible Information

TL;DR

This paper introduces hierarchical instance tracking, a new task that involves tracking object instances and their hierarchical relationships, supported by a novel benchmark dataset with diverse categories and challenging evaluation results.

Contribution

The paper presents the first benchmark dataset for hierarchical instance tracking, enabling research on tracking objects and parts with hierarchical relationships.

Findings

The dataset contains 2,765 entities across 40 categories.

Seven model variants were evaluated, revealing the task's difficulty.

The dataset is publicly available for further research.

Abstract

We propose a novel task, hierarchical instance tracking, which entails tracking all instances of predefined categories of objects and parts, while maintaining their hierarchical relationships. We introduce the first benchmark dataset supporting this task, consisting of 2,765 unique entities that are tracked in 552 videos and belong to 40 categories (across objects and parts). Evaluation of seven variants of four models tailored to our novel task reveals the new dataset is challenging. Our dataset is available at https://vizwiz.org/tasks-and-datasets/hierarchical-instance-tracking/