A vector-based, multidimensional scanpath similarity measure

A great need exists in many fields of eye-tracking research for a robust and general method for scanpath comparisons. Current measures either quantize scanpaths in space (string editing measures like the Levenshtein distance) or in time (measures based on attention maps). This paper proposes a new pairwise scanpath similarity measure. Unlike previous measures that either use AOI sequences or forgo temporal order, the new measure defines scanpaths as a series of geometric vectors and compares temporally aligned scanpaths across several dimensions: shape, fixation position, length, direction, and fixation duration. This approach offers more multifaceted insights to how similar two scanpaths are. Eight fictitious scanpath pairs are tested to elucidate the strengths of the new measure, both in itself and compared to two of the currently most popular measures - the Levenshtein distance and attention map correlation. CR Categories: I.5.3 [Pattern Recognition]: Clustering-Similarity Measures...

• Type: Journal
• Year: 2010
• Where: ETRA
• Authors: Halszka Jarodzka, Kenneth Holmqvist, Marcus Nyström
• Keywords: Biometrics, ETRA 2010, Levenshtein Distance, Pattern Recognition, Scanpath Similarity Measure