21 papers · ranked by Valyu relevance
Pradyumn Patil, Vishwajeet Pawar, Yashraj Pawar, Shruti Pisal
— Video content classification is an important research content in computer vision, which is widely used in many fields, such as image and video retrieval, computer vision. This paper presents a model that is a combination of Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN) which develops, trains…
Yilin Wang, Jiayi Ye
—Video classification and analysis is always a popular and challenging field in computer vision. It is more than just simple image classification due to the correlation with respect to the semantic contents of subsequent frames brings difficulties for video analysis. In this literature review, we summarized some…
Han Guangyu
With the rapid development of information technology, digital content shows an explosive growth trend. Sports video classification is of great significance for digital content archiving in the server. Therefore, the accurate classification of sports video categories is realized by using deep neural network algorithm…
Alexander M. Conway, Ian N. Durbach, Alistair McInnes, Robert N. Harris
Video data are widely collected in ecological studies but manual annotation is a challenging and time-consuming task, and has become a bottleneck for scientific research. Classification models based on convolutional neural networks (CNNs) have proved successful in annotating images, but few applications have extended…
Hao Ye, Zuxuan Wu, Rui-Wei Zhao, Xi Wang + 2 more
'Xiangyang Xue'] Videos contain very rich semantic information. Traditional hand-crafted features are known to be inadequate in analyzing complex video semantics. Inspired by the huge success of the deep learning methods in analyzing image, audio and text data, significant efforts are recently being devoted to the…
Nuo Pang, Songlin Guo, Ming Yan, Chien Aun Chan + 2 more
'Anastasios Doulamis' 'Zhe-Ming Lu'] The explosive growth of online short videos has brought great challenges to the efficient management of video content classification, retrieval, and recommendation. Video features for video management can be extracted from video image frames by various algorithms, and they have been…
Jonathan Attard, Dylan Seychell
—News videos require efficient content organisation and retrieval systems, but their unstructured nature poses significant challenges for automated processing. This paper presents a comprehensive comparative analysis of image, video, and audio classifiers for automated news video segmentation. This work presents the…
Mikołaj Leszczuk, Łukasz Dudek, Marcin Witkowski
The VQiPS (Video Quality in Public Safety) Working Group, supported by the U.S. Department of Homeland Security, has been developing a user guide for public safety video applications. According to VQiPS, five parameters have particular importance influencing the ability to achieve a recognition task. They are: usage…
Roberta Vrskova, Patrik Kamencay, Robert Hudec, Peter Sykora + 1 more
'Antonio Fernández-Caballero'] Currently, three-dimensional convolutional neural networks (3DCNNs) are a popular approach in the field of human activity recognition. However, due to the variety of methods used for human activity recognition, we propose a new deep-learning model in this paper. The main objective of our…
Pedro V. A. de Freitas, Paulo Renato da Costa Mendes, Gabriel N. P. dos Santos, Antonio José G. Busson + 3 more
'Gabriel N. P. dos Santos' 'Antonio José G. Busson' 'Álan L. V. Guedes' 'Sérgio Colcher' 'Ruy Luiz Milidiú'] Due to the extensive use of video-sharing platforms and services for their storage, the amount of such media on the internet has become massive. This volume of data makes it difficult to control the kind of…
Carl Harris, Kelly R. Finn, Peter U. Tse
The identification of behavior in video is a critical but time-consuming component in many areas of animal behavior research. Here, we introduce DeepAction, a deep learning-based toolbox for automatically annotating animal behavior in video. Our approach uses features extracted from raw video frames by a pretrained…
Jolyon Troscianko, Thomas A. O’Shea-Wheller, James Galloway, Kevin J. Gaston
Here we introduce BehaveAI, a biologically inspired video analysis framework that integrates static and motion information through a novel colour-from-motion encoding strategy. This method translates object movement – direction, speed, and acceleration – into colour gradients, enabling both human annotators and…
Mohd Haris Lye, Nouar AlDahoul, Hezerul Abdul Karim, Eui Chul Lee
Vidos from a first-person or egocentric perspective offer a promising tool for recognizing various activities related to daily living. In the egocentric perspective, the video is obtained from a wearable camera, and this enables the capture of the person’s activities in a consistent viewpoint. Recognition of activity…
Filip Rybansky, Sadegh Rahmaniboldaji, Andrew Gilbert, Frank Guerin + 2 more
Humans recognize everyday actions without conscious effort despite challenges such as poor viewing conditions and visual similarity between actions. Yet the visual features contributing to action recognition remain unclear. To address this, we combined semantic modelling and feature reduction methods to identify…
Pablo Negre, Ricardo S. Alonso, Alfonso González-Briones, Javier Prieto + 2 more
'Javier Prieto' 'Sara Rodríguez-González' 'Zhe-Ming Lu'] Physical aggression is a serious and widespread problem in society, affecting people worldwide. It impacts nearly every aspect of life. While some studies explore the root causes of violent behavior, others focus on urban planning in high-crime areas. Real-time…
Weiyao Lin, Ming–Ting Sun, Hongxiang Li, Zhenzhong Chen + 2 more
'Bing Zhou'] Abstract—In this paper, a macroblock classification method is proposed for various video processing applications involving motions. Based on the analysis of the Motion Vector field in the compressed video, we propose to classify Macroblocks of each video frame into different classes and use this class…
Talha Dilber, Mehmet Serdar Güzel, Erkan Bostancı
— In today's world, the amount of data produced in every field has increased at an unexpected level. In the face of increasing data, the importance of data processing has increased remarkably. Our resource topic is on the processing of video data, which has an important place in increasing data, and the production of…
Qifeng Qiao, Peter A. Beling
We propose a multiple instance learning approach to contentbased retrieval of classroom video for the purpose of supporting human assessing the learning environment. The key element of our approach is a mapping between the semantic concepts of the assessment system and features of the video that can be measured using…
Batyrkhan Omarov, Sergazi Narynov, Zhandos Zhumanov, Aidana Gumar + 2 more
'Mariyam Khassanova' 'Wenbing Zhao'] We investigate and analyze methods to violence detection in this study to completely disassemble the present condition and anticipate the emerging trends of violence discovery research. In this systematic review, we provide a comprehensive assessment of the video violence detection…
Peter Rennert, Oisin Mac Aodha, Matthew Piper, Gabriel Brostow
Background Scientific insight is often sought by recording and analyzing large quantities of video. While easy access to cameras has increased the quantity of collected videos, the rate at which they can be analyzed remains a major limitation. Often, bench scientists struggle with the most basic problem that there is…
Jordan C. Thompson, James H. Griffin, Renée Link
Multimedia approaches, including short instructional videos, are complementary to traditional modes of instruction such as in-person lecture and written procedures. We describe the creation and implementation of Quick Reference (QR) instructional videos in an undergraduate organic chemistry laboratory (OCL) setting for…