Image and Video Technology by Manoranjan Paul Carlos Hitoshi & Qingming Huang

Author:Manoranjan Paul, Carlos Hitoshi & Qingming Huang
Language: eng
Format: epub
Publisher: Springer International Publishing, Cham

2.3 Content and Resolution Invariant Operation on Features

Let us first consider the content (left in Fig. 5) and resolution (right in Fig. 5) based unprocessed L of two example sequences e.g. Poznan_Street and Newspaper presented in Fig. 5. The calculated variations between the highest and lowest values are 41.72% and 28.63% according to the contents and resolutions respectively. Now, the content invariant operation follows a number of steps. First, we figure out the L of the PGPs as mentioned in Sect. 2.2; Second, calculate the average of potential gaze plot (x) and (y) and entitle it by the centre coordinate C(x,y); Third, with respect to C(x,y), we calculate the Euclidean distance of all PGPs and sort the values of length by lowest to the highest order. The rationality of this ordering scheme is due to prioritize the foveal central concentration on pixels by partially avoiding the long surrounded parafoveal, or perifoveal fixations [27] that may incur even with attentive eye browsing; Fourth, to determine the object motion area, we take the average of first sorted values ( in this test since it could help the QMET in obtaining the highest score) which is the foreseen radius of captured affective region; Fifth, the radius is then employed as a divisor of calculated lengths for each potential gaze plots in the First step.

Fig. 5.The video content and resolution based unprocessed Length

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