1,503 Hits in 7.4 sec

Semi-Automatic Annotation of Objects in Visual-Thermal Video

Amanda Berg, Joakim Johnander, Flavie Durand de Gevigney, Jorgen Ahlberg, Michael Felberg
2019 2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW)  
In this work, a recursive, semi-automatic annotation method for video is presented.  ...  Deep learning requires large amounts of annotated data. Manual annotation of objects in video is, regardless of annotation type, a tedious and time-consuming process.  ...  Remote Thermography (2013-5703), the project ELLIIT (the Strategic Area for ICT research, funded by the Swedish Government), the Wallenberg AI, Autonomous Systems and Software Program (WASP), and the Visual  ... 
doi:10.1109/iccvw.2019.00277 dblp:conf/iccvw/BergJGAF19 fatcat:myy6s4bvpfdgrlil5wc3bbasnq

Effect of Annotation Errors on Drone Detection with YOLOv3 [article]

Aybora Koksal, Kutalmis Gokalp Ince, A. Aydin Alatan
2020 arXiv   pre-print
Even if the details of such semi-automatic annotation processes for most of these datasets are not known precisely, especially for the video annotations, some automated labeling processes are usually employed  ...  In this work, different types of annotation errors for object detection problem are simulated and the performance of a popular state-of-the-art object detector, YOLOv3, with erroneous annotations during  ...  Human operators preferred to use automatically corrected annotations for 66 videos over 100 thermal videos in dataset.  ... 
arXiv:2004.01059v3 fatcat:wyetbg7kijfplnjmtqqljhxz3u

A Survey on Machine Learning Techniques for Auto Labeling of Video, Audio, and Text Data [article]

Shikun Zhang, Omid Jafari, Parth Nagarkar
2021 arXiv   pre-print
In this survey paper, we provide a review of previous techniques that focuses on optimized data annotation and labeling for video, audio, and text data.  ...  Machine learning has been utilized to perform tasks in many different domains such as classification, object detection, image segmentation and natural language analysis.  ...  This novel approach is evaluated on a subset of the RGBT-234 visual-thermal dataset.  ... 
arXiv:2109.03784v1 fatcat:uu55zfmtajcvdjekxeaue76izy

Object Detection from Thermal Infrared and Visible Light Cameras in Search and Rescue Scenes

Adrian Banuls, Anthony Mandow, Ricardo Vazquez-Martin, Jesus Morales, Alfonso Garcia-Cerezo
2020 2020 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR)  
The goal of this paper is to explore the use of thermal and visible light images for automatic object detection in SAR scenes.  ...  Visual object recognition is a fundamental challenge for reliable search and rescue (SAR) robots, where vision can be limited by lighting and other harsh environmental conditions in disaster sites.  ...  In particular, we explore automatic object detection in SAR scenes with TIR images and their complementarity with visible images.  ... 
doi:10.1109/ssrr50563.2020.9292593 fatcat:7nnlvlsxvvdfxkdnmhesj2j3jq

Establishing the fundamentals for an elephant early warning and monitoring system

Matthias Zeppelzauer, Angela S. Stoeger
2015 BMC Research Notes  
Our visual detection method shows that tracking elephants in wildlife videos (of different sizes and postures) is feasible and particularly robust at near distances.  ...  In sight, their distinct visual appearance makes them a good candidate for visual monitoring.  ...  Additionally, methods from the analysis layer may assist biologists in the annotation of field data based on the proposal of annotation tags (semi-automatic annotation).  ... 
doi:10.1186/s13104-015-1370-y pmid:26338528 pmcid:PMC4558827 fatcat:44cqae5bl5cipdvr73riuahqze

FieldSAFE: Dataset for Obstacle Detection in Agriculture

Mikkel Kragh, Peter Christiansen, Morten Laursen, Morten Larsen, Kim Steen, Ole Green, Henrik Karstoft, Rasmus Jørgensen
2017 Sensors  
The dataset comprises approximately 2 hours of raw sensor data from a tractor-mounted sensor system in a grass mowing scenario in Denmark, October 2016.  ...  All obstacles have ground truth object labels and geographic coordinates.  ...  Finally, the moving obstacles were manually annotated in each frame of one of the videos using the vatic video annotation tool [22] .  ... 
doi:10.3390/s17112579 pmid:29120383 pmcid:PMC5713196 fatcat:fnjzk6f23rdi7lgzxgsspfpodq

Deep learning for automatic target recognition with real and synthetic infrared maritime imagery

Samuel Westlake, Timothy N. Volonakis, James Jackman, David B. James, Andy Sherriff, Judith Dijk
2020 Artificial Intelligence and Machine Learning in Defense Applications II  
Experiments demonstrated that supplementing the training data with a small sample of semi-labelled pseudo-IR imagery caused a marked improvement in performance.  ...  Supervised deep learning algorithms are re-defining the state-of-the-art for object detection and classification.  ...  Inclusion of semi-labelled pseudo-IR images With the aim of maximising the impact of semi-labelled visual-spectrum data, the third approach used a set of data transforms for the conversion of visual-spectrum  ... 
doi:10.1117/12.2573774 fatcat:xyarmqwjs5fllpxiwl2dtfqxfe

A Comprehensive Survey of Video Datasets for Background Subtraction

Rudrika Kalsotra, Sakshi Arora
2019 IEEE Access  
subtraction is an effective method of choice when it comes to detection of moving objects in videos and has been recognized as a breakthrough for the wide range of applications of intelligent video analytics  ...  The video datasets are presented in chronological order of their appearance.  ...  A semi-automatic method named Cascaded CNN based on multi-scale CNN with a cascaded architecture was designed by Wang et al. [118] in order to segment moving objects from the surveillance videos.  ... 
doi:10.1109/access.2019.2914961 fatcat:thr65j4uivehpgxtkwbsqi3yc4

Author Index

2010 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition  
Object and Human Pose in Human-Object Interaction Activities Connecting Modalities: Semi-supervised Segmentation and Annotation of Images Using Unaligned Text Corpora Felzenszwalb, Pedro F.  ...  Ruiz Workshop: Tensor-Jet: A Tensorial Representation of Local Binary Gaussian Jet Maps Herwana, Cipta Workshop: Annotation and Taxonomy of Gestures in Lecture Videos Hess, Harald Increasing Depth  ... 
doi:10.1109/cvpr.2010.5539913 fatcat:y6m5knstrzfyfin6jzusc42p54

Review on Social Behavior Analysis of Laboratory Animals: From Methodologies to Applications [article]

Ziping Jiang, Paul L. Chazot, Richard Jiang
2022 arXiv   pre-print
To mitigate the spend for annotating data, researchers turn to computer vision techniques for automatic label algorithms, since most of the data are recorded visually.  ...  The objective of this work is to provide a thorough investigation of related work, furnishing biologists with a scratch of efficient animal behaviour detection methods.  ...  To alleviate their burden, computer vision approaches are then introduced for automatic annotating.  ... 
arXiv:2206.12651v1 fatcat:fdappp4cvzdc7j3alukc7r3zt4

RGB-T Object Tracking:Benchmark and Baseline [article]

Chenglong Li, Xinyan Liang, Yijuan Lu, Nan Zhao, Jin Tang
2018 arXiv   pre-print
RGB-Thermal (RGB-T) object tracking receives more and more attention due to the strongly complementary benefits of thermal information to visible data.  ...  In particular, the tracked object is represented with a graph with image patches as nodes.  ...  It demonstrates the importance of thermal data in visual tracking. 3) Low Resolution: Although deep learning is a powerful tool in feature representation, it usually performs not well for objects with  ... 
arXiv:1805.08982v1 fatcat:jxkhfxbelnfbli7sfzynvwh5cm

VCIP 2020 Index

2020 2020 IEEE International Conference on Visual Communications and Image Processing (VCIP)  
On 2D-3D Image Feature Detections for Image To-Geometry Registration in Virtual Dental Mod Prawiro, Herman An Empirical Study of Emotion Recognition fro Thermal Video Based on Deep Neural Network  ...  People Zhang, Jian Automatic Sheep Counting by Multi-object Tracking Zhang, Jian Wearable Visually Assistive Device for Blind People to Appreciate Real-world Scene and Screen Image Zhang,  ... 
doi:10.1109/vcip49819.2020.9301896 fatcat:bdh7cuvstzgrbaztnahjdp5s5y

LLVIP: A Visible-infrared Paired Dataset for Low-light Vision [article]

Xinyu Jia, Chuang Zhu, Minzhen Li, Wenqi Tang, Shengjie Liu, Wenli Zhou
2022 arXiv   pre-print
The experimental results demonstrate the complementary effect of fusion on image information, and find the deficiency of existing algorithms of the three visual tasks in very low-light conditions.  ...  It is very challenging for various visual tasks such as image fusion, pedestrian detection and image-to-image translation in low light conditions due to the loss of effective target areas.  ...  Acknowledgments This work was supported in part by 111 Project of China (B17007), and in part by the National Natural Science Foundation of China (61602011).  ... 
arXiv:2108.10831v3 fatcat:2sbtlk5tljd3dj6qghvt7anlyu

Weighted Sparse Representation Regularized Graph Learning for RGB-T Object Tracking

Chenglong Li, Nan Zhao, Yijuan Lu, Chengli Zhu, Jin Tang
2017 Proceedings of the 2017 ACM on Multimedia Conference - MM '17  
In this paper, we propose a novel graph model, called weighted sparse representation regularized graph, to learn a robust object representation using multispectral (RGB and thermal) data for visual tracking  ...  pair: 8K). 2) The alignment between RGB-T video pairs is highly accurate, which does not need pre-and post-processing. 3) The occlusion levels are annotated for analyzing the occlusion-sensitive performance  ...  Annotation For large scale performance evaluation of different RGB-T tracking algorithms, we collect 210 RGB-T video pairs, each containing a RGB video and a thermal video.  ... 
doi:10.1145/3123266.3123289 dblp:conf/mm/LiZLZT17 fatcat:42ltlcdzoner7g4xd7xjt5vruq


А. Axyonov, D. Ryumin, I. Kagirov
2021 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
Generally, gesture recognition is a processing of a video sequence, which helps to extract information on movements of any articulator (a part of the human body) in time and space.  ...  The paper also proposes a new method of multimodal sign recognition, which is distinguished by the analysis of spatio-temporal visual features of SL units (i.e. lexemes).  ...  In the last step, all collected multimodal data must be (semi) automatically annotated and segmented at the level of minimum gesture units (classes) in a semiautomatic or automatic way.  ... 
doi:10.5194/isprs-archives-xliv-2-w1-2021-7-2021 fatcat:e4zvtzofpvca7fyrczbafnemdi
« Previous Showing results 1 — 15 out of 1,503 results