A. Manju¹, A. Revathi², M. Arivukarasi¹, S. Hariharan³, V. Umarani⁴, Shih-Yu Chen^5,*, Jin Wang⁶

Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 905-920, 2023, DOI:10.32604/iasc.2023.038444 - 29 April 2023

Abstract With the proliferation of the internet, big data continues to grow exponentially, and video has become the largest source. Video big data introduces many technological challenges, including compression, storage, transmission, analysis, and recognition. The increase in the number of multimedia resources has brought an urgent need to develop intelligent methods to organize and process them. The integration between Semantic link Networks and multimedia resources provides a new prospect for organizing them with their semantics. The tags and surrounding texts of multimedia resources are used to measure their semantic association. Two evaluation methods including clustering and… More >

S. Prabu^1,*, J. M. Gnanasekar²

Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 2257-2271, 2023, DOI:10.32604/iasc.2023.029877 - 19 July 2022

Abstract Object detection plays a vital role in the video surveillance systems. To enhance security, surveillance cameras are now installed in public areas such as traffic signals, roadways, retail malls, train stations, and banks. However, monitoring the video continually at a quicker pace is a challenging job. As a consequence, security cameras are useless and need human monitoring. The primary difficulty with video surveillance is identifying abnormalities such as thefts, accidents, crimes, or other unlawful actions. The anomalous action does not occur at a higher rate than usual occurrences. To detect the object in a video,… More >

A. Balasundaram^1,*, Golda Dilip², M. Manickam³, Arun Kumar Sivaraman⁴, K. Gurunathan⁵, R. Dhanalakshmi⁶, S. Ashokkumar⁷

Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 693-704, 2022, DOI:10.32604/iasc.2022.022241 - 17 November 2021

Abstract In the present world, video surveillance methods play a vital role in observing the activities that take place across secured and unsecured environment. The main aim with which a surveillance system is deployed is to spot abnormalities in specific areas like airport, military, forests and other remote areas, etc. A new block-based strategy is represented in this paper. This strategy is used to identify unusual circumstances by examining the pixel-wise frame movement instead of the standard object-based approaches. The density and also the speed of the movement is extorted by utilizing optical flow. The proposed More >

Junchuan Yang^*

Journal of New Media, Vol.2, No.4, pp. 137-148, 2020, DOI:10.32604/jnm.2020.014278 - 23 December 2020

Abstract Person Re-identification (re-ID) is a hot research topic in the field of computer vision now, which can be regarded as a sub-problem of image retrieval. The goal of person re-ID is to give a monitoring pedestrian image and retrieve other images of the pedestrian across the device. At present, person re-ID is mainly divided into two categories. One is the traditional methods, which relies heavily on manual features. The other is to use deep learning technology to solve. Because traditional methods mainly rely on manual feature, they cannot adapt well to a complex environment with More >

Tong Jiang^*

Journal of New Media, Vol.2, No.2, pp. 45-60, 2020, DOI:10.32604/jnm.2020.09823 - 21 August 2020

Abstract Recently, person Re-identification (person Re-id) has attracted more and more attention, which has become a research focus of computer vision community. Person Re-id is used to ascertain whether the target pedestrians captured by cameras in different positions at different moments are the same person or not. However, due to the influence of various complex factors, person Re-id still has a lot of holes to be filled. In this paper, we first review the research process of person Re-id, and then, two kinds of mainstream methods for person Re-id are introduced respectively, according to the different More >

Jinxing Niu^{1, *}, Yajie Jiang¹, Yayun Fu¹, Tao Zhang¹, Nicola Masini²

CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 807-816, 2020, DOI:10.32604/cmc.2020.011044 - 23 July 2020

Abstract Video surveillance system is used in various fields such as transportation and social life. The bad weather can lead to the degradation of the video surveillance image quality. In rainy environment, the raindrops and the background are mixed, which lead to make the image degradation, so the removal of the raindrops has great significance for image restoration. In this article, after analyzing the inter-frame difference method in detecting and removing raindrops, a background difference method is proposed based on Gaussian model. In this method, the raindrop is regarded as a moving object relative to the… More >