Abstract
The main objective of this chapter is to summarize the authors’ recent work which studied the human-computer interaction for sketch-based passwords. However, before discussing the previous results, the features used specifically for implementation of SKS are discussed, and an overview of the database used for the HCI study (and some experiments and results in the subsequent chapter) is provided. The features used for the application of sketch-based passwords incorporates four fundamental properties: (1) shape, (2) direction, (3) order, and (4) pressure, which comprise a local 5D feature descriptor at every sketch sample point. The database used for this HCI study was constructed by the authors in (Riggan et al., A human factors study of graphical passwords using biometrics. Proc. of the 36th German Conf. on Pattern Recognition, 2014). This database considers a sufficiently large and complete set of users and many variations of sketch-based passwords. The previous HCI is useful to understand the connection between human perception and certain similarity measures, specifically for sketch-based authentication.
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Notes
- 1.
The term complexity, here, refers to the complexity of the drawing itself. There are many possible definition for complexity of a drawing, such as the polynomial order of an appropriate regression model or the number of self-intersections.
- 2.
Distributions for H1, D2, and H2 are similar the distributions shown here.
- 3.
For the D1, H1, D2, and H2 histograms, the reference sketches (i.e. used to build model) come from the D1 session and testing is performed on the sketch from the respective session. Note for the D1 session the scores corresponding to identical sketches are removed from the histogram to reduce result bias.
- 4.
SKS may be more robust than the Frechet distance because it has a broad definition of similar and more narrow definition of different.
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Riggan, B., Snyder, W., Wang, C. (2014). Human-Computer Interaction. In: Fundamentals of Sketch-Based Passwords. SpringerBriefs in Computer Science. Springer, Cham. https://doi.org/10.1007/978-3-319-13629-5_5
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DOI: https://doi.org/10.1007/978-3-319-13629-5_5
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