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"Background subtraction" is an old technique for finding moving objects in a video sequence for example, cars driving on a freeway. The idea is that subtracting the current image from a timeaveraged background image will leave only…

Computer Vision and Pattern Recognition · Computer Science 2013-02-08 Nir Friedman , Stuart Russell

The robustness of semantic segmentation on edge cases of traffic scene is a vital factor for the safety of intelligent transportation. However, most of the critical scenes of traffic accidents are extremely dynamic and previously unseen,…

Computer Vision and Pattern Recognition · Computer Science 2021-12-10 Jiaming Zhang , Kailun Yang , Rainer Stiefelhagen

Event-based cameras have recently drawn the attention of the Computer Vision community thanks to their advantages in terms of high temporal resolution, low power consumption and high dynamic range, compared to traditional frame-based…

Computer Vision and Pattern Recognition · Computer Science 2018-03-22 Amos Sironi , Manuele Brambilla , Nicolas Bourdis , Xavier Lagorce , Ryad Benosman

Event cameras are novel sensors that report brightness changes in the form of a stream of asynchronous "events" instead of intensity frames. They offer significant advantages with respect to conventional cameras: high temporal resolution,…

Computer Vision and Pattern Recognition · Computer Science 2019-06-19 Henri Rebecq , René Ranftl , Vladlen Koltun , Davide Scaramuzza

Event-based camera is a bio-inspired vision sensor that records intensity changes (called event) asynchronously in each pixel. As an instance of event-based camera, Dynamic and Active-pixel Vision Sensor (DAVIS) combines a standard camera…

Computer Vision and Pattern Recognition · Computer Science 2019-04-29 Yuhu Guo , Han Xiao , Yidong Chen , Xiaodong Shi

In this paper, an event-based tracker is presented. Inspired by recent advances in asynchronous processing of individual events, we develop a direct matching scheme that aligns spatial distributions of events at different times. More…

Computer Vision and Pattern Recognition · Computer Science 2024-10-08 Maria Zafeiri , Georgios Evangelidis , Emmanouil Psarakis

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

The performance of an adaptive tracking-by-detection algorithm not only depends on the classification and updating processes but also on the sampling. Typically, such trackers select their samples from the vicinity of the last predicted…

Computer Vision and Pattern Recognition · Computer Science 2018-06-08 Kourosh Meshgi , Maryam Sadat Mirzaei , Shigeyuki Oba

Non-uniform image deblurring is a challenging task due to the lack of temporal and textural information in the blurry image itself. Complementary information from auxiliary sensors such event sensors are being explored to address these…

Computer Vision and Pattern Recognition · Computer Science 2022-08-25 Patricia Vitoria , Stamatios Georgoulis , Stepan Tulyakov , Alfredo Bochicchio , Julius Erbach , Yuanyou Li

Recent studies on motion estimation have advocated an optimized motion representation that is globally consistent across the entire video, preferably for every pixel. This is challenging as a uniform representation may not account for the…

Computer Vision and Pattern Recognition · Computer Science 2024-07-17 Rui Li , Dong Liu

Given a raw video sequence taken from a freely-moving camera, we study the problem of decomposing the observed 3D scene into a static background and a dynamic foreground containing the objects that move in the video sequence. This task is…

Computer Vision and Pattern Recognition · Computer Science 2021-10-20 Vadim Tschernezki , Diane Larlus , Andrea Vedaldi

Event-based structured light systems have recently been introduced as an exciting alternative to conventional frame-based triangulation systems for the 3D measurements of diffuse surfaces. Important benefits include the fast capture speed…

Computer Vision and Pattern Recognition · Computer Science 2025-06-12 Aniket Dashpute , Jiazhang Wang , James Taylor , Oliver Cossairt , Ashok Veeraraghavan , Florian Willomitzer

Unsupervised video segmentation plays an important role in a wide variety of applications from object identification to compression. However, to date, fast motion, motion blur and occlusions pose significant challenges. To address these…

Computer Vision and Pattern Recognition · Computer Science 2018-09-05 Yuan-Ting Hu , Jia-Bin Huang , Alexander G. Schwing

This paper proposes a novel method for segmentation of images by hierarchical multilevel thresholding. The method is global, agglomerative in nature and disregards pixel locations. It involves the optimization of the ratio of the unbiased…

Computer Vision and Pattern Recognition · Computer Science 2007-12-27 Sreechakra Goparaju , Jayadev Acharya , Ajoy K. Ray , Jaideva C. Goswami

Event cameras are novel vision sensors that output pixel-level brightness changes ("events") instead of traditional video frames. These asynchronous sensors offer several advantages over traditional cameras, such as, high temporal…

Computer Vision and Pattern Recognition · Computer Science 2022-07-08 Guillermo Gallego , Mathias Gehrig , Davide Scaramuzza

Event cameras are gaining popularity due to their unique properties, such as their low latency and high dynamic range. One task where these benefits can be crucial is real-time object detection. However, RGB detectors still outperform…

Computer Vision and Pattern Recognition · Computer Science 2023-11-10 Lei Li , Alexander Liniger , Mario Millhaeusler , Vagia Tsiminaki , Yuanyou Li , Dengxin Dai

Real-time motion detection in non-stationary scenes is a difficult task due to dynamic background, changing foreground appearance and limited computational resource. These challenges degrade the performance of the existing methods in…

Computer Vision and Pattern Recognition · Computer Science 2018-11-22 Junjie Huang , Wei Zou , Zheng Zhu , Jiagang Zhu

Event-cameras have emerged as a revolutionary technology with a high temporal resolution that far surpasses standard active pixel cameras. This technology draws biological inspiration from photoreceptors and the initial retinal synapse.…

Computer Vision and Pattern Recognition · Computer Science 2024-12-09 Victoria Clerico , Shay Snyder , Arya Lohia , Md Abdullah-Al Kaiser , Gregory Schwartz , Akhilesh Jaiswal , Maryam Parsa

Temporal action segmentation classifies the action of each frame in (long) video sequences. Due to the high cost of frame-wise labeling, we propose the first semi-supervised method for temporal action segmentation. Our method hinges on…

Computer Vision and Pattern Recognition · Computer Science 2021-12-09 Dipika Singhania , Rahul Rahaman , Angela Yao

Event cameras are emerging vision sensors and their advantages are suitable for various applications such as autonomous robots. Contrast maximization (CMax), which provides state-of-the-art accuracy on motion estimation using events, may…

Computer Vision and Pattern Recognition · Computer Science 2024-03-05 Shintaro Shiba , Yoshimitsu Aoki , Guillermo Gallego
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