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http://dx.doi.org/10.5392/IJoC.2014.10.1.001

Construction of a Video Dataset for Face Tracking Benchmarking Using a Ground Truth Generation Tool  

Do, Luu Ngoc (Department of Computer Engineering Chonnam National University)
Yang, Hyung Jeong (Department of Computer Engineering Chonnam National University)
Kim, Soo Hyung (Department of Computer Engineering Chonnam National University)
Lee, Guee Sang (Department of Computer Engineering Chonnam National University)
Na, In Seop (Department of Computer Engineering Chonnam National University)
Kim, Sun Hee (Carnegie Mellon University)
Publication Information
International Journal of Contents / v.10, no.1, 2014 , pp. 1-11 More about this Journal
Abstract
In the current generation of smart mobile devices, object tracking is one of the most important research topics for computer vision. Because human face tracking can be widely used for many applications, collecting a dataset of face videos is necessary for evaluating the performance of a tracker and for comparing different approaches. Unfortunately, the well-known benchmark datasets of face videos are not sufficiently diverse. As a result, it is difficult to compare the accuracy between different tracking algorithms in various conditions, namely illumination, background complexity, and subject movement. In this paper, we propose a new dataset that includes 91 face video clips that were recorded in different conditions. We also provide a semi-automatic ground-truth generation tool that can easily be used to evaluate the performance of face tracking systems. This tool helps to maintain the consistency of the definitions for the ground-truth in each frame. The resulting video data set is used to evaluate well-known approaches and test their efficiency.
Keywords
Face Tracking; Ground-truth; Face Video Dataset;
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