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Anomalous Event Detection in Traffic Video Based on Sequential Temporal Patterns of Spatial Interval Events

2015 KSII Transactions on Internet and Information Systems  
In this paper, a Lossy Count based Sequential Temporal Pattern mining approach (LC-STP) is proposed for detecting spatio-temporal abnormal events (such as a traffic violation at junction) from sequences  ...  The proposed approach relies mainly on spatial abstractions of each object, mining frequent temporal patterns in a sequence of video frames to form a regular temporal pattern.  ...  The proposed approach is analyzed to detect both intra-and inter-temporal spatial events.  ... 
doi:10.3837/tiis.2015.01.010 fatcat:w7mfslopivhx3poabipnvyebxa

Real-centric Consistency Learning for Deepfake Detection [article]

Ruiqi Zha, Zhichao Lian, Qianmu Li, Siqi Gu
2022 arXiv   pre-print
At the sample level, we take the procedure of deepfake synthesis into consideration and propose a novel forgery semantical-based pairing strategy to mine latent generation-related features.  ...  Therefore, inspired by contrastive representation learning, we tackle the deepfake detection problem through learning the invariant representations of both classes and propose a novel real-centric consistency  ...  Related work Deepfake Detection.  ... 
arXiv:2205.07201v1 fatcat:mtpr3z566jef7e5xb2d3aok3py

Toward Dynamic Scene Understanding by Hierarchical Motion Pattern Mining

Lei Song, Fan Jiang, Zhongke Shi, Rafael Molina, Aggelos K. Katsaggelos
2014 IEEE transactions on intelligent transportation systems (Print)  
For example, in a video monitoring intersection, without any prior knowledge about the traffic rules in the specific scene.  ...  It is highly desirable to analyze the motion patterns and obtain some high-level interpretation of the semantic relations content.  ...  A motion pattern the problem of analyzing and understanding dynamic video scenes. A multi level motion pattern mining approach is proposed.  ... 
doi:10.1109/tits.2014.2299403 fatcat:duj6boicbbgpjhhimhv4ey6eh4

Recent Trends and Research Issues in Video Association Mining

Vijayakumar, Nedunchezhian
2011 The International Journal of Multimedia & Its Applications  
Discovering association rules between items in a large video database plays a considerable role in the video data mining research areas.  ...  With the ever-growing digital libraries and video databases, it is increasingly important to understand and mine the knowledge from video database automatically.  ...  Many video mining approaches have been proposed for extracting useful knowledge from video database.  ... 
doi:10.5121/ijma.2011.3405 fatcat:otbefjxy4vaynmosfmqmre5qai

A Review of Co-saliency Detection Technique: Fundamentals, Applications, and Challenges [article]

Dingwen Zhang, Huazhu Fu, Junwei Han, Ali Borji, Xuelong Li
2017 arXiv   pre-print
Specifically, we provide an overview of some related computer vision works, review the history of co-saliency detection, summarize and categorize the major algorithms in this research area, discuss some  ...  We expect this review to be beneficial to both fresh and senior researchers in this field, and give insights to researchers in other related areas regarding the utility of co-saliency detection algorithms  ...  RELATED AREAS In this section, we discuss some related areas to co-saliency detection including saliency object detection, object co-segmentation, weakly supervised localization, and video saliency.  ... 
arXiv:1604.07090v5 fatcat:j7zqwqaowndrbcuoazzizkuqr4

ClassMiner: Mining Medical Video Content Structure and Events Towards Efficient Access and Scalable Skimming

Xingquan Zhu, Jianping Fan, Walid G. Aref, Ahmed K. Elmagarmid
2002 Workshop on Research Issues on Data Mining and Knowledge Discovery  
Then, audio and video processing techniques are integrated to mine event information, such as dialog, presentation and clinical operation, among the detected scenes.  ...  To achieve more efficient video indexing and access, we introduce a video content structure and event mining framework.  ...  Moreover, the constructed tree structures do not make sense to the video database indexing. Detecting similar or unusual patterns is not the only objective for video data mining.  ... 
dblp:conf/dmkd/ZhuFAE02 fatcat:sayluw5d3ze27mtvn6rbwvgfjq

[Invited Paper] A Review of Web Image Mining

Keiji Yanai
2015 ITE Transactions on Media Technology and Applications  
of visual concept database for image/video recognition, (2) Web image application for visual concept analysis and data-driven computer graphics, and (3) real-world sensing through Web images to detect  ...  In this paper, we review works related to big visual data on the Web in the literature of computer vision and multimedia research regarding the following points: (1) Web image acquisition for construction  ...  As relations, NEIL can learn object-object relations including part-of and instance-of relations, and object-attribute, scene-object, and scene-attribute relations.  ... 
doi:10.3169/mta.3.156 fatcat:gduk25dp7nedvm65xurbwzdu3y

Context-Based Structure Mining Methodology for Static Object Re-Identification in Broadcast Content

Krishna Kumar Thirukokaranam Chandrasekar, Steven Verstockt
2021 Applied Sciences  
Subsequently, this paper extends the structure mining pipeline to re-ID objects in broadcast videos such as SOAPs.  ...  By implementing pre-trained models for object and place detection, the pipeline was evaluated using metrics for shot and scene detection on benchmark datasets, such as RAI.  ...  Related Work This work elaborates the role of semantics in video analysis tasks such as video structure mining and re-ID.  ... 
doi:10.3390/app11167266 fatcat:ax2wopyjsvdo3lz7hik2vegiqe

Semantic Based Video Retrieval System: Survey

2018 Iraqi Journal of Science  
The video retrieval system is used for finding the users' desired video among a huge number of available videos on the Internet or database.  ...  In addition to its present a generic review of techniques that has been proposed to solve the semantic gap as the major scientific problem in semantic based video retrieval.  ...  Video Association Mining Video association mining can be defined as the process of detecting unknown relationships between different events and identifying the more frequent association patterns for different  ... 
doi:10.24996/ijs.2018.59.2a.12 fatcat:6fvq6pygqzglbptl4czxpzbjbm

Probing Visual-Audio Representation for Video Highlight Detection via Hard-Pairs Guided Contrastive Learning [article]

Shuaicheng Li, Feng Zhang, Kunlin Yang, Lingbo Liu, Shinan Liu, Jun Hou, Shuai Yi
2022 arXiv   pre-print
Video highlight detection is a crucial yet challenging problem that aims to identify the interesting moments in untrimmed videos.  ...  A hard-pairs sampling strategy is further employed to mine the hard samples for improving feature discrimination in HPCL.  ...  We propose a novel visual-audio framework for highlight detection.  ... 
arXiv:2206.10157v1 fatcat:p7maa74v25dblbj7yk7tiyu67q

Transitive Invariance for Self-supervised Visual Representation Learning [article]

Xiaolong Wang, Kaiming He, Abhinav Gupta
2017 arXiv   pre-print
Specifically, we propose to generate a graph with millions of objects mined from hundreds of thousands of videos.  ...  For object detection, we achieve 63.2% mAP on PASCAL VOC 2007 using Fast R-CNN (compare to 67.3% with ImageNet pre-training).  ...  on the mined moving objects in the videos as in [61] .  ... 
arXiv:1708.02901v3 fatcat:enmp5l5zezfpzc5spyfx64bueq

Event detection in sports video based on generative-discriminative models

Yi Ding, Guoliang Fan
2009 Proceedings of the 1st ACM international workshop on Events in multimedia - EiMM '09  
We also propose a unified video mining framework where event detection is formulated as two inter-related inference problems associated with two different machine learning tools.  ...  We study event detection in the context of sports video mining that involves a three-layer semantic space, i.e., low-level visual features, mid-level semantic structures, and high-level semantics (or events  ...  The authors also thank the anonymous reviewers for their valuable comments and suggestions that improved this paper.  ... 
doi:10.1145/1631024.1631030 dblp:conf/mm/DingF09 fatcat:ntey5qzg6vc6veavmrgicuuaf4

Abnormal Event Detection via Feature Expectation Subgraph Calibrating Classification in Video Surveillance Scenes

Ou Ye, Jun Deng, Zhenhua Yu, Tao Liu, Lihong Dong
2020 IEEE Access  
Finally, the experiments on a common dataset named UCSDped1 and a coal mining video dataset in comparison with some existing works demonstrate that the performance of the proposed method is better than  ...  In order to address the above issues, we propose an abnormal event detection hybrid modulation method via feature expectation subgraph calibrating classification in video surveillance scenes in this paper  ...  For example, the study in [30] proposes an approach that relies mainly on spatial abstractions of each object, mining frequent temporal patterns in a sequence of video frames to form a regular temporal  ... 
doi:10.1109/access.2020.2997357 fatcat:yrytr47smnapdla7cwo7sbyqma

Video Anomaly Detection Using Pre-Trained Deep Convolutional Neural Nets and Context Mining [article]

Chongke Wu, Sicong Shao, Cihan Tunc, Salim Hariri
2020 arXiv   pre-print
Our anomaly detection model makes decisions based on the high-level features derived from the selected embedded computer vision models such as object classification and object detection.  ...  Anomaly detection is critically important for intelligent surveillance systems to detect in a timely manner any malicious activities.  ...  We choose the COCO dataset to make it as the baseline for the context mining comparison. 2) Context Mining Even though pre-trained models provide useful features, we still need the inter-relationship  ... 
arXiv:2010.02406v1 fatcat:qtnkz4ktm5ebpdznorectb7rky

Natural Language Descriptions for Human Activities in Video Streams

Nouf Alharbi, Yoshihiko Gotoh
2017 Proceedings of the 10th International Conference on Natural Language Generation  
Detected action classes rendered as verbs, participant objects converted to noun phrases, visual properties of detected objects rendered as adjectives and spatial relations between objects rendered as  ...  The proposed video descriptions framework evaluated on the NLDHA dataset using ROUGE scores and human judgment evaluation.  ...  Finally, the compact CORE-9 representation is used to extract the spatial and temporal aspects for multiple inter-related object bodies by analysing the nine cores and six intervals in each binary relation  ... 
doi:10.18653/v1/w17-3512 dblp:conf/inlg/HarbiG17 fatcat:y25fk3r525dm3gay277lknepta
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