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Recent years have seen an explosion of interest in analyzing the motion of objects in video data as a way for students to connect the concepts of physics to something tangible like a video recording of an experiment. A variety of software…

This paper presents a new way of getting high-quality saliency maps for video, using a cheaper alternative to eye-tracking data. We designed a mouse-contingent video viewing system which simulates the viewers' peripheral vision based on the…

计算机视觉与模式识别 · 计算机科学 2019-07-02 Vitaliy Lyudvichenko , Dmitriy Vatolin

We propose ProTracker, a novel framework for accurate and robust long-term dense tracking of arbitrary points in videos. Previous methods relying on global cost volumes effectively handle large occlusions and scene changes but lack…

计算机视觉与模式识别 · 计算机科学 2025-03-11 Tingyang Zhang , Chen Wang , Zhiyang Dou , Qingzhe Gao , Jiahui Lei , Baoquan Chen , Lingjie Liu

An interferometric fluorescent microscope and a novel theoretic image reconstruction approach were developed and used to obtain super-resolution images of live biological samples and to enable dynamic real time tracking. The tracking…

Video-based eye tracking is a valuable technique in various research fields. Numerous open-source eye tracking algorithms have been developed in recent years, primarily designed for general application with many different camera types.…

计算机视觉与模式识别 · 计算机科学 2017-06-28 Terence Brouns

Humans use context and scene knowledge to easily localize moving objects in conditions of complex illumination changes, scene clutter and occlusions. In this paper, we present a method to leverage human knowledge in the form of annotated…

计算机视觉与模式识别 · 计算机科学 2016-04-20 Archith J. Bency , S. Karthikeyan , Carter De Leo , Santhoshkumar Sunderrajan , B. S. Manjunath

We propose a system that uses video as the input to track the position of objects relative to their surrounding environment in real-time. The neural network employed is trained on a 100% synthetic dataset coming from our own automated…

计算机视觉与模式识别 · 计算机科学 2020-10-30 David Albarracín , Jesús Hormigo , José David Fernández

Object tracking is one of the most important problems in computer vision. The aim of video tracking is to extract the trajectories of a target or object of interest, i.e. accurately locate a moving target in a video sequence and…

计算机视觉与模式识别 · 计算机科学 2020-03-19 Niloufar Salehi Dastjerdi , M. Omair Ahmad

A robust algorithm solution is proposed for tracking an object in complex video scenes. In this solution, the bootstrap particle filter (PF) is initialized by an object detector, which models the time-evolving background of the video signal…

计算机视觉与模式识别 · 计算机科学 2015-09-29 Yi Dai , Bin Liu

Eyeframe lens tracing is an important process in the optical industry that requires sub-millimeter precision to ensure proper lens fitting and optimal vision correction. Traditional frame tracers rely on mechanical tools that need precise…

计算机视觉与模式识别 · 计算机科学 2026-02-19 Manel Guzmán , Antonio Agudo

Reducing the number of pixels in video signals while maintaining quality needed for recovering the trace of an object using Compressive Sensing is main subject of this work. Quality of frames, from video that contains moving object, are…

计算机视觉与模式识别 · 计算机科学 2019-03-18 Marijana Kracunov , Milica Bastica , Jovana Tesovic

Single particle tracking is essential in many branches of science and technology, from the measurement of biomolecular forces to the study of colloidal crystals. Standard current methods rely on algorithmic approaches: by fine-tuning…

软凝聚态物质 · 物理学 2018-12-07 Saga Helgadottir , Aykut Argun , Giovanni Volpe

Driver inattention is a large problem on the roads around the world. The objective of this project was to develop an eye tracking algorithm with sufficient computational efficiency and accuracy, to successfully realize when the driver was…

计算机视觉与模式识别 · 计算机科学 2019-08-26 Matthew Kowal , Gillian Sandison , Len Yabuki-Soh , Raner la Bastide

Purpose: In this paper, we present a novel approach for online object tracking in laparoscopic cholecystectomy (LC) surgical videos, targeting localisation and tracking of critical anatomical structures and instruments. Our method addresses…

计算机视觉与模式识别 · 计算机科学 2026-03-10 Subhadeep Koley , Abdolrahim Kadkhodamohammadi , Santiago Barbarisi , Danail Stoyanov , Imanol Luengo

Visual tracking is a fundamental problem in computer vision. Recently, some deep-learning-based tracking algorithms have been achieving record-breaking performances. However, due to the high complexity of deep learning, most deep trackers…

计算机视觉与模式识别 · 计算机科学 2017-01-04 Xinyu Wang , Hanxi Li , Yi Li , Fumin Shen , Fatih Porikli

In endoscopic procedures, surgeons work with live video streams from the inside of their subjects. A main source for documentation of procedures are still frames from the video, identified and taken during the surgery. However, with growing…

Most tracking-by-detection methods employ a local search window around the predicted object location in the current frame assuming the previous location is accurate, the trajectory is smooth, and the computational capacity permits a search…

计算机视觉与模式识别 · 计算机科学 2016-05-09 Gao Zhu , Fatih Porikli , Hongdong Li

Most tracking-by-detection methods employ a local search window around the predicted object location in the current frame assuming the previous location is accurate, the trajectory is smooth, and the computational capacity permits a search…

计算机视觉与模式识别 · 计算机科学 2015-12-01 Gao Zhu , Fatih Porikli , Hongdong Li

Object tracking is the cornerstone of many visual analytics systems. While considerable progress has been made in this area in recent years, robust, efficient, and accurate tracking in real-world video remains a challenge. In this paper, we…

计算机视觉与模式识别 · 计算机科学 2018-06-19 Saeed Ranjbar Alvar , Ivan V. Bajić

With the advance of fluorescence imaging technologies, recently cell biologists are able to record the movement of protein vesicles within a living cell. Automatic tracking of the movements of these vesicles become key for qualitative…

定量方法 · 定量生物学 2015-06-09 Min Xu
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