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Related papers: A Framework for Pupil Tracking with Event Cameras

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We propose a new video camouflaged object detection (VCOD) framework that can exploit both short-term dynamics and long-term temporal consistency to detect camouflaged objects from video frames. An essential property of camouflaged objects…

Computer Vision and Pattern Recognition · Computer Science 2022-03-16 Xuelian Cheng , Huan Xiong , Deng-Ping Fan , Yiran Zhong , Mehrtash Harandi , Tom Drummond , Zongyuan Ge

Smooth pursuit eye movements provide meaningful insights and information on subject's behavior and health and may, in particular situations, disturb the performance of typical fixation/saccade classification algorithms. Thus, an automatic…

Computer Vision and Pattern Recognition · Computer Science 2015-11-25 Thiago Santini , Wolfgang Fuhl , Thomas Kübler , Enkelejda Kasneci

Eye-tracking analysis plays a vital role in medical imaging, providing key insights into how radiologists visually interpret and diagnose clinical cases. In this work, we first analyze radiologists' attention and agreement by measuring the…

Objects moving at high speed along complex trajectories often appear in videos, especially videos of sports. Such objects elapse non-negligible distance during exposure time of a single frame and therefore their position in the frame is not…

Computer Vision and Pattern Recognition · Computer Science 2020-06-03 Jan Kotera , Denys Rozumnyi , Filip Šroubek , Jiří Matas

Accurate detection and tracking of objects is vital for effective video understanding. In previous work, the two tasks have been combined in a way that tracking is based heavily on detection, but the detection benefits marginally from the…

Computer Vision and Pattern Recognition · Computer Science 2018-11-28 Zheng Zhang , Dazhi Cheng , Xizhou Zhu , Stephen Lin , Jifeng Dai

Real-time tracking is an important problem in computer vision in which most methods are based on the conventional cameras. Neuromorphic vision is a concept defined by incorporating neuromorphic vision sensors such as silicon retinas in…

Computer Vision and Pattern Recognition · Computer Science 2015-10-20 Hongmin Li , Pei Jing , Guoqi Li

The goal of video segmentation is to turn video data into a set of concrete motion clusters that can be easily interpreted as building blocks of the video. There are some works on similar topics like detecting scene cuts in a video, but…

Computer Vision and Pattern Recognition · Computer Science 2019-03-07 Hajar Sadeghi Sokeh , Vasileios Argyriou , Dorothy Monekosso , Paolo Remagnino

Long-term object detection requires the integration of frame-based results over several seconds. For non-deformable objects, long-term detection is often addressed using object detection followed by video tracking. Unfortunately, tracking…

Computer Vision and Pattern Recognition · Computer Science 2021-10-15 Sravani Teeparthi , Venkatesh Jatla , Marios S. Pattichis , Sylvia Celedon Pattichis , Carlos LopezLeiva

Event cameras provide a natural and data efficient representation of visual information, motivating novel computational strategies towards extracting visual information. Inspired by the biological vision system, we propose a behavior driven…

Computer Vision and Pattern Recognition · Computer Science 2024-10-30 Nan Cai , Pia Bideau

Detecting objects in a video is a compute-intensive task. In this paper we propose CaTDet, a system to speedup object detection by leveraging the temporal correlation in video. CaTDet consists of two DNN models that form a cascaded…

Computer Vision and Pattern Recognition · Computer Science 2019-02-20 Huizi Mao , Taeyoung Kong , William J. Dally

The Human visual perception of the world is of a large fixed image that is highly detailed and sharp. However, receptor density in the retina is not uniform: a small central region called the fovea is very dense and exhibits high…

Computer Vision and Pattern Recognition · Computer Science 2017-01-26 Alon Hazan , Yuval Harel , Ron Meir

Event cameras are bio-inspired sensors that capture the per-pixel intensity changes asynchronously and produce event streams encoding the time, pixel position, and polarity (sign) of the intensity changes. Event cameras possess a myriad of…

Computer Vision and Pattern Recognition · Computer Science 2024-04-12 Xu Zheng , Yexin Liu , Yunfan Lu , Tongyan Hua , Tianbo Pan , Weiming Zhang , Dacheng Tao , Lin Wang

Event cameras are neuromorphically inspired sensors that sparsely and asynchronously report brightness changes. Their unique characteristics of high temporal resolution, high dynamic range, and low power consumption make them well-suited…

Computer Vision and Pattern Recognition · Computer Science 2024-12-30 Haitao Meng , Chonghao Zhong , Sheng Tang , Lian JunJia , Wenwei Lin , Zhenshan Bing , Yi Chang , Gang Chen , Alois Knoll

With the development of widely available commercial eye trackers, the use of eye tracking and pupillometry have become prevalent tools in cognitive research, both in industry and academia. However, dealing with pupil recordings often proves…

Signal Processing · Electrical Eng. & Systems 2020-11-11 Helia Relaño-Iborra , Per Bækgaard

Event cameras capture per-pixel brightness changes with microsecond resolution, offering continuous motion information lost between RGB frames. However, existing event-based motion estimators depend on large-scale synthetic data that often…

Computer Vision and Pattern Recognition · Computer Science 2026-03-25 Jini Yang , Eunbeen Hong , Soowon Son , Hyunkoo Lee , Sunghwan Hong , Sunok Kim , Seungryong Kim

Neuromorphic vision or event vision is an advanced vision technology, where in contrast to the visible camera that outputs pixels, the event vision generates neuromorphic events every time there is a brightness change which exceeds a…

Computer Vision and Pattern Recognition · Computer Science 2023-01-11 Waseem Shariff , Muhammad Ali Farooq , Joe Lemley , Peter Corcoran

This paper presents the novel combination of a visual transformer style patch classifier with saccaded local attention. A novel optimisation paradigm for training object models is also presented, rather than the optimisation function…

Computer Vision and Pattern Recognition · Computer Science 2022-10-18 Willem. T. Pye , David. A. Sinclair

When watching the image of a natural scene on a computer screen, observers initially move their eyes towards the center of the image --- a reliable experimental finding termed central fixation bias. This systematic tendency in eye guidance…

Neurons and Cognition · Quantitative Biology 2017-06-22 Lars Oliver Martin Rothkegel , Hans Arne Trukenbrod , Heiko Herbert Schütt , Felix Alexander Wichmann , Ralf Engbert

We present an approach to estimating camera rotation in crowded, real-world scenes from handheld monocular video. While camera rotation estimation is a well-studied problem, no previous methods exhibit both high accuracy and acceptable…

Computer Vision and Pattern Recognition · Computer Science 2023-09-18 Fabien Delattre , David Dirnfeld , Phat Nguyen , Stephen Scarano , Michael J. Jones , Pedro Miraldo , Erik Learned-Miller

Gaze may enhance the robustness of lie detectors but remains under-studied. This study evaluated the efficacy of AI models (using fixations, saccades, blinks, and pupil size) for detecting deception in Concealed Information Tests across two…

Human-Computer Interaction · Computer Science 2025-05-06 Valentin Foucher , Santiago de Leon-Martinez , Robert Moro