Abstract

Video cameras with interlaced scan sensors find applications in a variety of tasks such as object tracking due to their lower overhead in terms of memory and the higher sensitivity in comparison to their counterparts that employ progressive scan sensors. Such cameras, however, suffer from noticeable interlacing artefacts that need to be corrected with appropriate de-interlacing methods before the target in the video can be accurately tracked. Despite this, the effect of de-interlacing methods on the object tracking accuracy has not yet been widely studied. In this work, the first comprehensive comparison of different de-interlacing methods is carried out in the context human computer interaction studies where precise finger tracking is required. Furthermore, we propose a semiautomatic sub-pixel annotation scheme to create precise ground truth for fingertip location, allowing the analysis of the impact of de-interlacing filters on tracking at sub-pixel level. The experimental part of the work showed that the de-interlacing filter by Pixop outperformed other filters that were evaluated. Moreover, the plausible benefits of sub-pixel precise tracking over pixel precise tracking in trajectory analysis were demonstrated.

Highlights

  • Human-Computer Interaction (HCI) is an endeavour that seeks to understand and transform our interactions with complex technological artefacts in order to make these interactions effective, efficient and more importantly, enjoyable

  • We explored a few intricate details concerning a computer vision based HCI experiment that were previously unexplored

  • We address the issue of sub-pixel annotation while allowing for human errors via our semiautomatic annotation scheme

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Summary

Introduction

Human-Computer Interaction (HCI) is an endeavour that seeks to understand and transform our interactions with complex technological artefacts in order to make these interactions effective, efficient and more importantly, enjoyable. A minor blemish associated with such a framework emanates due to the inability of the generic object trackers to accurately localize the hand and finger movements to the required level of precision leading to a significant number of overshooting errors [6]. This apathy of object trackers towards sub-pixel accuracy is warranted as most object tracking algorithms are geared towards tasks that consider robustness and real time processing, over accuracy, as more critical factors in evaluating the success of a tracking algorithm. In touch screen usability studies, subpixel accuracy takes precedence as even minor errors in target localization can lead to huge errors, especially while considering parallax errors [7]

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