Assessment of Advertising Effectiveness Through Audience’s Eye Movements

2010 ◽  
Author(s):  
Shize Jin ◽  
Yong Zeng ◽  
Chun Wang
Keyword(s):  
Eye Movements ◽  
Advertising Effectiveness ◽  
Effectiveness Evaluation ◽  
Design Phase ◽  
High Quality ◽  
Final Performance ◽  
Movement Data ◽  
Rating Method ◽  
Survey Results ◽  
Novel Method

The evaluation of advertisement effectiveness during the advertisement design phase and pre-launch phase is critical for the advertisement’s success in the targeted market. This evaluation should predict advertisement’s final performance as accurately as possible. In today’s advertisement business, questionnaire-based evaluation methods, such as attitude and opinion rating are widely used. To obtain good survey results, high quality questionnaires and proper interviewing procedures have to be developed with the support of the competent execution and supervision. These activities are usually costly even though some of them can be conducted online. This paper proposes a novel method for assessing the advertisement effectiveness through the automated capturing and analyzing of audiences’ eye movements. This method is based on the assumption that some attributes of audiences’ eye movements are correlated to their visual attention defined in the context of advertisement effectiveness. To validate our research hypotheses, experiments were conducted. In the experiments, subjects were required to watch several advertisements in sequence and the subjects’ eye movement data were collected simultaneously. By analyzing the data patterns and comparing them with the effectiveness evaluation obtained from questionnaire-based method, we found that the proposed method produces similar evaluations to those resulted from the traditional attitude and opinion rating method.

Age Differences in Eye Movements During Reading: Degenerative Problems or Compensatory Strategy?

2019 ◽  
Vol 24 (4) ◽  
pp. 297-311
Author(s):  
José David Moreno ◽  
José A. León ◽  
Lorena A. M. Arnal ◽  
Juan Botella
Keyword(s):  
Eye Movements ◽  
Eye Movement ◽  
Meta Analysis ◽  
Age Groups ◽  
Behavioral Changes ◽  
Aging Effects ◽  
Movement Data ◽  
Sentence Reading ◽  
The Difference ◽  
Eye Movements During Reading

Abstract. We report the results of a meta-analysis of 22 experiments comparing the eye movement data obtained from young ( Mage = 21 years) and old ( Mage = 73 years) readers. The data included six eye movement measures (mean gaze duration, mean fixation duration, total sentence reading time, mean number of fixations, mean number of regressions, and mean length of progressive saccade eye movements). Estimates were obtained of the typified mean difference, d, between the age groups in all six measures. The results showed positive combined effect size estimates in favor of the young adult group (between 0.54 and 3.66 in all measures), although the difference for the mean number of fixations was not significant. Young adults make in a systematic way, shorter gazes, fewer regressions, and shorter saccadic movements during reading than older adults, and they also read faster. The meta-analysis results confirm statistically the most common patterns observed in previous research; therefore, eye movements seem to be a useful tool to measure behavioral changes due to the aging process. Moreover, these results do not allow us to discard either of the two main hypotheses assessed for explaining the observed aging effects, namely neural degenerative problems and the adoption of compensatory strategies.

scholarly journals Directed Gaze Trajectories for Biometric Presentation Attack Detection

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1394
Author(s):  
Asad Ali ◽  
Sanaul Hoque ◽  
Farzin Deravi
Keyword(s):  
Eye Movements ◽  
Visual Stimuli ◽  
Attack Detection ◽  
Movement Data ◽  
Biometric Systems ◽  
Planar Geometries ◽  
Presentation Attack Detection

Presentation attack artefacts can be used to subvert the operation of biometric systems by being presented to the sensors of such systems. In this work, we propose the use of visual stimuli with randomised trajectories to stimulate eye movements for the detection of such spoofing attacks. The presentation of a moving visual challenge is used to ensure that some pupillary motion is stimulated and then captured with a camera. Various types of challenge trajectories are explored on different planar geometries representing prospective devices where the challenge could be presented to users. To evaluate the system, photo, 2D mask and 3D mask attack artefacts were used and pupillary movement data were captured from 80 volunteers performing genuine and spoofing attempts. The results support the potential of the proposed features for the detection of biometric presentation attacks.

scholarly journals Saliency-Based Gaze Visualization for Eye Movement Analysis

Sensors ◽  
2021 ◽  
Vol 21 (15) ◽  
pp. 5178
Author(s):  
Sangbong Yoo ◽  
Seongmin Jeong ◽  
Seokyeon Kim ◽  
Yun Jang
Keyword(s):  
Eye Movements ◽  
Visual Attention ◽  
Eye Movement ◽  
Visual Stimuli ◽  
Saliency Map ◽  
Gaze Behavior ◽  
The Gaze ◽  
Movement Data ◽  
Visual Clues ◽  
Human Visual Attention

Gaze movement and visual stimuli have been utilized to analyze human visual attention intuitively. Gaze behavior studies mainly show statistical analyses of eye movements and human visual attention. During these analyses, eye movement data and the saliency map are presented to the analysts as separate views or merged views. However, the analysts become frustrated when they need to memorize all of the separate views or when the eye movements obscure the saliency map in the merged views. Therefore, it is not easy to analyze how visual stimuli affect gaze movements since existing techniques focus excessively on the eye movement data. In this paper, we propose a novel visualization technique for analyzing gaze behavior using saliency features as visual clues to express the visual attention of an observer. The visual clues that represent visual attention are analyzed to reveal which saliency features are prominent for the visual stimulus analysis. We visualize the gaze data with the saliency features to interpret the visual attention. We analyze the gaze behavior with the proposed visualization to evaluate that our approach to embedding saliency features within the visualization supports us to understand the visual attention of an observer.

The “Orienting Reflex” as an Input Indicator in “Subliminal” Perception

1972 ◽  
Vol 35 (1) ◽  
pp. 103-110
Author(s):  
Phillip Kleespies ◽  
Morton Wiener
Keyword(s):  
Eye Movements ◽  
Eye Movement ◽  
Exposure Duration ◽  
Visual Input ◽  
Orienting Reflex ◽  
Subliminal Perception ◽  
Thematic Content ◽  
Movement Data ◽  
Report Data ◽  
Input Indicator

This study explored (1) for evidence of visual input at so-called “subliminal” exposure durations, and (2) whether the response, if any, was a function of the thematic content of the stimulus. Thematic content (threatening versus non-threatening) and stimulus structure (angular versus curved) were varied independently under “subliminal,” “part-cue,” and “identification” exposure conditions. With Ss' reports and the frequency and latency of first eye movements (“orienting reflex”) as input indicators, there was no evidence of input differences which are a function of thematic content at any exposure duration, and the “report” data were consistent with the eye-movement data.

scholarly journals Strategic Team AI Path Plans: Probabilistic Pathfinding

2008 ◽  
Vol 2008 ◽  
pp. 1-6 ◽  
Author(s):  
Tng C. H. John ◽  
Edmond C. Prakash ◽  
Narendra S. Chaudhari
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Computer Games ◽  
Fitness Function ◽  
New Method ◽  
High Quality ◽  
Plan Generation ◽  
Novel Method ◽  
Games And Simulations

This paper proposes a novel method to generate strategic team AI pathfinding plans for computer games and simulations using probabilistic pathfinding. This method is inspired by genetic algorithms (Russell and Norvig, 2002), in that, a fitness function is used to test the quality of the path plans. The method generates high-quality path plans by eliminating the low-quality ones. The path plans are generated by probabilistic pathfinding, and the elimination is done by a fitness test of the path plans. This path plan generation method has the ability to generate variation or different high-quality paths, which is desired for games to increase replay values. This work is an extension of our earlier work on team AI: probabilistic pathfinding (John et al., 2006). We explore ways to combine probabilistic pathfinding and genetic algorithm to create a new method to generate strategic team AI pathfinding plans.

scholarly journals Modelling Gaze Behaviour in Subtitle Processing

2021 ◽  
Vol 4 (1) ◽  
pp. 71-95
Author(s):  
Juha Lång ◽  
Hana Vrzakova ◽  
Lauri Mehtätalo
Keyword(s):  
Eye Movements ◽  
Cognitive Processing ◽  
Audiovisual Material ◽  
Gaze Behavior ◽  
Contributing Factors ◽  
Movement Data ◽  
Starting Point ◽  
Gaze Behaviour ◽  
Television Documentary ◽  
Participant Group

  One of the main rules of subtitling states that subtitles should be formatted and timed so that viewers have enough time to read and understand the text but also to follow the picture. In this paper we examine the factors that influence the time viewers spend looking at subtitles. We concentrate on the lexical and structural properties of subtitles. The participant group (N = 14) watched a television documentary with Russian narration and Finnish subtitles (the participants’ native language), while their eye movements were tracked. Using a linear mixed-effects model, we identified significant effects of subtitle duration and character count on the time participants spent looking at the subtitles. The model also revealed significant inter-individual differences, despite the fact that the participant group was seemingly homogeneous. The findings underline the complexity of subtitled audiovisual material as a stimulus of cognitive processing. We provide a starting point for more comprehensive modelling of the factors involved in gaze behaviour when watching subtitled content. Lay summary Subtitles have become a popular method for watching foreign series and films even in countries that have traditionally used dubbing in this regard. Because subtitles are visible to the viewer a short, limited time, they should be composed so that they are easy to read, and that the viewer has time to also follow the image. Nevertheless, the factors that have impact the time it takes to read a subtitle is not very well known. We wanted to find out what makes people who are watching subtitled television shows spend more time gazing at the subtitles? To answer this question, we recorded the eye movements of 14 participants when they were watching a short, subtitled television documentary. We created a statistical model of the gaze behavior from the eye movement data and found that both the length of the subtitle and the time the subtitle is visible are separate contributing factors. We also discovered large differences between individual viewers. Our conclusion is that people process subtitled content in very different ways, but there are some common tendencies. Our model can be seen as solid starting point for comprehensive modelling of gaze behavior of people watching subtitled audiovisual material.

scholarly journals WALD-EM: Wald Accumulation for Locations and Durations of Eye Movements

2020 ◽  
Author(s):  
Šimon Kucharský ◽  
Daan Roelof van Renswoude ◽  
Maartje Eusebia Josefa Raijmakers ◽  
Ingmar Visser
Keyword(s):  
Eye Movements ◽  
Eye Movement ◽  
Empirical Research ◽  
Process Models ◽  
Movement Behavior ◽  
Movement Data ◽  
Fixation Durations ◽  
Research Cycle ◽  
Fixation Locations ◽  
Basic Characteristics

Describing, analyzing and explaining patterns in eye movement behavior is crucial for understanding visual perception. Further, eye movements are increasingly used in informing cognitive process models. In this article, we start by reviewing basic characteristics and desiderata for models of eye movements. Specifically, we argue that there is a need for models combining spatial and temporal aspects of eye-tracking data (i.e., fixation durations and fixation locations), that formal models derived from concrete theoretical assumptions are needed to inform our empirical research, and custom statistical models are useful for detecting specific empirical phenomena that are to be explained by said theory. In this article, we develop a conceptual model of eye movements, or specifically, fixation durations and fixation locations, and from it derive a formal statistical model --- meeting our goal of crafting a model useful in both the theoretical and empirical research cycle. We demonstrate the use of the model on an example of infant natural scene viewing, to show that the model is able to explain different features of the eye movement data, and to showcase how to identify that the model needs to be adapted if it does not agree with the data. We conclude with discussion of potential future avenues for formal eye movement models.

scholarly journals Case Study of Effectiveness Evaluation of Staff Training Courses in Refah Bank

2017 ◽  
Vol 7 (4) ◽  
pp. 1870-1873
Author(s):  
E. Yousefian ◽  
A. Chitsaz ◽  
B. Karimpour
Keyword(s):  
Staff Training ◽  
Effectiveness Evaluation ◽  
Confounding Factors ◽  
Two Factors ◽  
Survey Results ◽  
Training Courses

One of the newest and most well-known train patterns for evaluating the effectiveness of in-service staffs training is Kircpatrick model. In this paper, the effectiveness of staff training courses of Refah-bank is evaluated. A questionnaire consisted of five components which include: reaction, learning, of behavior, the results and the innovation in role of confounding factors is handed out. The survey results show that three factors (reactions, behavior and innovation) have a significant effect on the teachings effectiveness according to Kircpatrick model. And that two factors (learning and results of the courses) have not a significant effect.

scholarly journals Automated Filtering of Eye Movements Using Dynamic AOI in Multiple Granularity Levels

2021 ◽  
Vol 12 (1) ◽  
pp. 49-64
Author(s):  
Gavindya Jayawardena ◽  
Sampath Jayarathna
Keyword(s):  
Eye Movements ◽  
Eye Tracking ◽  
Eye Movement ◽  
Eye Gaze ◽  
Movement Analysis ◽  
Movement Data ◽  
Bounding Boxes ◽  
Multiple Granularity ◽  
Instance Segmentation ◽  
Segmentation Models

Eye-tracking experiments involve areas of interest (AOIs) for the analysis of eye gaze data. While there are tools to delineate AOIs to extract eye movement data, they may require users to manually draw boundaries of AOIs on eye tracking stimuli or use markers to define AOIs. This paper introduces two novel techniques to dynamically filter eye movement data from AOIs for the analysis of eye metrics from multiple levels of granularity. The authors incorporate pre-trained object detectors and object instance segmentation models for offline detection of dynamic AOIs in video streams. This research presents the implementation and evaluation of object detectors and object instance segmentation models to find the best model to be integrated in a real-time eye movement analysis pipeline. The authors filter gaze data that falls within the polygonal boundaries of detected dynamic AOIs and apply object detector to find bounding-boxes in a public dataset. The results indicate that the dynamic AOIs generated by object detectors capture 60% of eye movements & object instance segmentation models capture 30% of eye movements.

scholarly journals Scaling High-Quality Pairwise Link-Based Similarity Retrieval on Billion-Edge Graphs

2022 ◽  
Vol 40 (4) ◽  
pp. 1-45
Author(s):  
Weiren Yu ◽  
Julie McCann ◽  
Chengyuan Zhang ◽  
Hakan Ferhatosmanoglu
Keyword(s):  
Web Search ◽  
Similarity Score ◽  
High Quality ◽  
Deterministic Method ◽  
Large Graphs ◽  
Guaranteed Accuracy ◽  
Semantic Difference ◽  
Speed Up ◽  
Novel Method ◽  
Search Quality

SimRank is an attractive link-based similarity measure used in fertile fields of Web search and sociometry. However, the existing deterministic method by Kusumoto et al. [ 24 ] for retrieving SimRank does not always produce high-quality similarity results, as it fails to accurately obtain diagonal correction matrix  D . Moreover, SimRank has a “connectivity trait” problem: increasing the number of paths between a pair of nodes would decrease its similarity score. The best-known remedy, SimRank++ [ 1 ], cannot completely fix this problem, since its score would still be zero if there are no common in-neighbors between two nodes. In this article, we study fast high-quality link-based similarity search on billion-scale graphs. (1) We first devise a “varied- D ” method to accurately compute SimRank in linear memory. We also aggregate duplicate computations, which reduces the time of [ 24 ] from quadratic to linear in the number of iterations. (2) We propose a novel “cosine-based” SimRank model to circumvent the “connectivity trait” problem. (3) To substantially speed up the partial-pairs “cosine-based” SimRank search on large graphs, we devise an efficient dimensionality reduction algorithm, PSR # , with guaranteed accuracy. (4) We give mathematical insights to the semantic difference between SimRank and its variant, and correct an argument in [ 24 ] that “if D is replaced by a scaled identity matrix (1-Ɣ)I, their top-K rankings will not be affected much”. (5) We propose a novel method that can accurately convert from Li et al.  SimRank ~{S} to Jeh and Widom’s SimRank S . (6) We propose GSR # , a generalisation of our “cosine-based” SimRank model, to quantify pairwise similarities across two distinct graphs, unlike SimRank that would assess nodes across two graphs as completely dissimilar. Extensive experiments on various datasets demonstrate the superiority of our proposed approaches in terms of high search quality, computational efficiency, accuracy, and scalability on billion-edge graphs.

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