Abstract:Videos and commercials produced for large audiences can elicit mixed opinions. We wondered whether this diversity is also reflected in the way individuals watch the videos. To answer this question, we presented 65 commercials with high production value to 25 individuals while recording their eye movements, and asked them to provide preference ratings for each video. We find that gaze positions for the most popular videos are highly correlated. To explain the correlations of eye movements, we model them as “int… Show more
“…In particular, we confirmed a positive association between fixation map consistency and scene memorability in both datasets (Fig. 3), consistent with previous research with static scenes (Khosla et al, 2015;Mancas & Le Meur, 2013) and videos (Burleson-Lesser et al, 2017;Christoforou et al, 2015). Moreover, the observed correlation values between fixation map consistency and scene memorability from the Edinburgh and FIGRIM datasets (0.25 [0.08,0.40] and 0.22 [0.14, 0.29], respectively) were very similar to the values reported by Khosla et al…”
Studying factors that contribute to scene memorability is important for understanding human vision and memory. Here we demonstrated in two different eye-tracking datasets that the higher the fixation map consistency (also called inter-observer congruency of fixation maps) of a scene, the higher its memorability is. To provide a mechanistic explanation for how a scene can produce more or less consistent fixation maps across viewers, we created a simple computational model by assuming some high signal regions in a scene that will attract more fixations than other regions (ambient noise). We then varied the amplitude of the signal relative to noise (SNR) to examine the relationship between SNR and fixation map consistency. Our model showed that the higher a scene’s SNR, the higher its fixation map consistency, suggesting that fixation map consistency reflects the SNR of a scene, an intrinsic scene property that can affect human vision and memory.
“…In particular, we confirmed a positive association between fixation map consistency and scene memorability in both datasets (Fig. 3), consistent with previous research with static scenes (Khosla et al, 2015;Mancas & Le Meur, 2013) and videos (Burleson-Lesser et al, 2017;Christoforou et al, 2015). Moreover, the observed correlation values between fixation map consistency and scene memorability from the Edinburgh and FIGRIM datasets (0.25 [0.08,0.40] and 0.22 [0.14, 0.29], respectively) were very similar to the values reported by Khosla et al…”
Studying factors that contribute to scene memorability is important for understanding human vision and memory. Here we demonstrated in two different eye-tracking datasets that the higher the fixation map consistency (also called inter-observer congruency of fixation maps) of a scene, the higher its memorability is. To provide a mechanistic explanation for how a scene can produce more or less consistent fixation maps across viewers, we created a simple computational model by assuming some high signal regions in a scene that will attract more fixations than other regions (ambient noise). We then varied the amplitude of the signal relative to noise (SNR) to examine the relationship between SNR and fixation map consistency. Our model showed that the higher a scene’s SNR, the higher its fixation map consistency, suggesting that fixation map consistency reflects the SNR of a scene, an intrinsic scene property that can affect human vision and memory.
“…With these two constraints determined by the data, we really only have 3 degrees of freedom remaining for optimization. Parameter µ n is directly specified by µ z (15). Parameters σ a and σ 2 n will be reduced to a single parameter, namely, the logarithm of the signal to noise ratio:…”
Section: Attention Modelmentioning
confidence: 99%
“…Previous studies have shown that eye movements are correlated across subjects during video presentation [11,12]. This inter-subject correlation (ISC) of eye-movements is elevated for dynamic, well-produced movies and video advertising [13][14][15], and is affected by the viewing task [16]. A variety of eye tracking measures have been used in educational research [17].…”
Experienced teachers pay close attention to their students, adjusting their teaching when students seem lost. This dynamic interaction is missing in online education. We propose to measure attention to online videos remotely by tracking eye movements, as we hypothesize that attentive students follow videos similarly with their eyes. Here we show that inter-subject correlation of eye movements during instructional video presentation is substantially higher for attentive students, and that eye movements are predictive of individual test scores on the material presented in the video. These findings replicate for videos in a variety of production styles, for intentional and incidental learning and for recall and comprehension questions alike. We reproduce the result using standard web cameras in a classroom setting, and with over 1,000 participants at-home without the need to transmit user data. Our results suggest that online education could be made adaptive to a student's level of attention in real-time.
“…The results showed that the end water of the Han River was used as the water source, and 110 species and 102 species of organic matter were detected in the wet and dry periods, respectively. Burlesonlesser et al [6] performs photocatalytic degradation of toxic and harmful organic wastewater by TiO 2 photocatalytic degradation, seawater desalination pretreatment and seafloor manganese nodules on organic pollutants. The research results provide valuable scientific theoretical basis and reference for industrial application in photocatalysis.…”
The problem of environmental pollution is becoming more and more serious with the rapid development of industry and economy, especially the organic matter pollution in water. Thermodynamic analysis method is used based on this to analyze and study the pollution and treatment process of water organic matter in this paper. By proposing that the pollution essence is caused by the uneven distribution of sub-energy, the effect of organic pollutants treatment in four kinds of water bodies in Shenzhen City was analyzed by graphite material adsorption from the perspective of thermodynamic analysis. The experimental results show that the degree of organic pollution in the Jia reservoir of Shenzhen City is from high to low: Dasha River, campus pond, Jia reservoir, and B reservoir. When the ionic strength is 0.04 M, pH is 3.0, graphene loading is 2.5%, and reduced graphene oxide dosage is 200 mg/L, the degradation efficiency of organic pollutants in water is as high as 96.25%.
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