An Advertisement Video Analysis System Based on Eye-Tracking

Zhang, Xuebai; Fan, Chih-Tien; Yuan, Shyan-Ming; Peng, Zih-You

doi:10.1109/smartcity.2015.118

Cited by 6 publications

(4 citation statements)

References 6 publications

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“…Ada sejumlah metode untuk mengukur pergerakan mata. Varian yang paling populer adalah menggunakan gambar video dari mana posisi mata diambil [4]. Ada juga metode lain yaitu menggunakan kumparan pencarian atau didasarkan pada elektrookulogram [5].…”

Section: Eye Trackingunclassified

Aplikasi Pengukuran Aktivitas Pengguna dalam Menjalankan Program Komputer menggunakan Eye Tracker

Dhita Diana Dewi

2023

Restikom

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Seiring perkembangan teknologi informasi, muncul beberapa bidang-bidang baru, salah satunya bidang aktivitas pengguna. Aspek ini kian menjadi penting sebagai penentu dari sebuah aplikasi untuk dapat berkompetisi didalam pasar dikarenakan banyaknya aplikasi pesaing yang muncul. Gerakan mata seorang pengguna bisa menjawab berbagai pertanyaan krusial yang bisa memberikan informasi terhadap permasalahan aplikasi sampai tingkat efektivitas tampilannya. Oleh karena itu, untuk memenuhi kebutuhan tersebut, maka diciptakanlah aplikasi pengukuran aktivitas pengguna menggunakan eye tracker. Penelitian ini menggunakan metode Usability Testing (UT) kepada aplikasi lain yaitu IZI lalu menggunakan metode blob detection untuk mendeteksi blob. Menggunakan metode Hue, Saturation, Value (HSV), program dapat mendeteksi blob dengan baik. Program ini menggunakan parameter hue sebesar 0.80 dan 1.00 untuk mask1, 0.005 dan 0.15 untuk mask2, dan value sebesar 0,01 dan 0.98 lalu difilter menggunakan median filter. Blob yang terdeteksi diubah ke bentuk dataframe lalu diambil parameter centroid, area, dan solidity-nya. Centroid dari tiap blob dibandingkan dan diukur jaraknya menggunakan rumus Euclidean distance untuk mendapatkan tingkat similaritasnya. Dari hasil penelitian, didapat 13 dari 14 blob target telah terpenuhi. Dari hasil tersebut dianalisis dan disimpulkan bahwa aplikasi IZI telah efektif secara tampilan.

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Section: Eye Trackingunclassified

Aplikasi Pengukuran Aktivitas Pengguna dalam Menjalankan Program Komputer menggunakan Eye Tracker

Dhita Diana Dewi

2023

Restikom

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“…Human viewers' gaze behaviour when watching videos reflects their perception processes and interpretation of the visual content [12][13][14]. Attempts have been made in the VQA literature to weight local distortions by existing saliency models [9,10].…”

Section: Introductionmentioning

confidence: 99%

Analysis of Video Quality Induced Spatio-Temporal Saliency Shifts

Dong

Zhang

et al. 2022

2022 IEEE International Conference on Image Processing (ICIP)

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Human viewers' eye movements reflect their perceptual responses to visual signals. Previous research has shown that distortions in videos cause spatio-temporal gaze shifts, which means gaze behaviour is related to video quality perception. It would be highly beneficial to understand gaze behaviour of viewing videos of varying perceived quality. However, little is known about the interactions between gaze, video content and distortions. In this paper, based on our eye-tracking database for video quality (SVQ160), we perform systematic analyses to reveal the impact of video content (VC) and time order (TO) on gaze shifts. Findings and quantitative methods for gaze behaviour can be used to develop advanced video quality metrics and video processing algorithms.

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“…Early studies assumed a fixed head pose, but they were extended to allow some head movement by adding complementary techniques [7,8]. Recent studies [4,9] combine head pose and eye information by a feature concatenation method. However, they use flexible face models to detect face and eye regions.…”

mentioning

confidence: 99%

“…Introduction: Gaze information has long been used in medical diagnosis [1], psychological analysis [2], human-computer interactions (HCI) [3], marketing [4], and driver state estimation [5]. Gaze estimation has been studied for decades.…”

mentioning

confidence: 99%

Head pose‐free gaze estimation using domain adaptation

Ahn

Seo

Choi

2021

Electronics Letters

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Human gaze information has been widely used in various areas, such as medical diagnosis and human-computer interactions (HCI). This study proposes a head pose-free 3D gaze estimation method using a deep convolutional neural network (DCNN). To infer gaze direction, only a small grayscale image is required without any special devices such as an infrared (IR) illuminator and RGBD sensor. A domain adaptation method to reduce the feature gap between real and synthetic image data is also proposed here. Moreover, a novel synthetic dataset (SynFace) that contains head poses, gaze directions, and facial landmarks is established and released. The proposed method outperforms state-of-the-art methods and achieves a mean error of less than 4 • .

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An Advertisement Video Analysis System Based on Eye-Tracking

Cited by 6 publications

References 6 publications

Aplikasi Pengukuran Aktivitas Pengguna dalam Menjalankan Program Komputer menggunakan Eye Tracker

Aplikasi Pengukuran Aktivitas Pengguna dalam Menjalankan Program Komputer menggunakan Eye Tracker

Analysis of Video Quality Induced Spatio-Temporal Saliency Shifts

Head pose‐free gaze estimation using domain adaptation

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