A Survey on Hardware Implementations of Visual Object Trackers

TL;DR

This survey reviews two decades of hardware implementations for visual object trackers, highlighting gaps in current research, especially for state-of-the-art algorithms, and emphasizing the need for performance measurement and detailed comparisons.

Contribution

It provides a comprehensive overview of hardware-based object tracking solutions, identifying research gaps and suggesting future directions in the field.

Findings

Lack of hardware implementations for recent tracking algorithms

Insufficient performance measurement of hardware trackers

Need for detailed hardware implementation comparisons

Abstract

Visual object tracking is an active topic in the computer vision domain with applications extending over numerous fields. The main sub-tasks required to build an object tracker (e.g. object detection, feature extraction and object tracking) are computation-intensive. In addition, real-time operation of the tracker is indispensable for almost all of its applications. Therefore, complete hardware or hardware/software co-design approaches are pursued for better tracker implementations. This paper presents a literature survey of the hardware implementations of object trackers over the last two decades. Although several tracking surveys exist in literature, a survey addressing the hardware implementations of the different trackers is missing. We believe this survey would fill the gap and complete the picture with the existing surveys of how to design an efficient tracker and point out the future directions researchers can follow in this field. We highlight the lack of hardware implementations for state-of-the-art tracking algorithms as well as for enhanced classical algorithms. We also stress the need for measuring the tracking performance of the hardware-based trackers. Additionally, enough details of the hardware-based trackers need to be provided to allow reasonable comparison between the different implementations.