A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
Filters
Graph-Based Correlated Topic Model for Trajectory Clustering in Crowded Videos
2018
2018 IEEE Winter Conference on Applications of Computer Vision (WACV)
Preserved Fulltext
Unlike previous works that depend on scenes prior, we extract trajectories and apply a spatio-temporal graph (STG) to uncover the spatial and temporal coherence between the trajectories during the learning ...
This paper presents a graph-based correlated topic model (GCTM) to learn and analyse motion patterns by trajectory clustering in a highly cluttered and crowded environment. ...
Many works have been proposed for trajectory clustering based on mid-level features learning. ...
doi:10.1109/wacv.2018.00118
dblp:conf/wacv/GhamdiG18
fatcat:v6khgdcde5gijbcew3hi75o2nm
Progressive Dictionary Learning With Hierarchical Predictive Structure for Low Bit-Rate Scalable Video Coding
2017
IEEE Transactions on Image Processing
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
On the other hand, scalable extension of conventional hybrid motion compensation-discrete cosine transform (MC-DCT) framework has been widely studied for scalable video coding. ...
This paper proposes a progressive dictionary learning framework with hierarchical predictive structure for scalable video coding, especially in low bitrate region. ...
The proposed framework for scalable video coding based on progressive dictionary learning. ...
doi:10.1109/tip.2017.2692882
pmid:28422683
pmcid:PMC5638692
fatcat:yrf6mgcpojezvjhmiuvmvqklne
A Gaussian Mixture Representation of Gesture Kinematics for On-Line Sign Language Video Annotation
[chapter]
2015
Lecture Notes in Computer Science
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
This work introduces a method to support SL annotations based on a motion descriptor that characterizes dynamic gestures in videos. ...
Then for each sub-region, a histogram of motion-cues occurrence is built, forming a frame-gesture descriptor which can be used for on-line annotation. ...
Conclusions This work introduced a new motion descriptor that is able to recognize motion gestures related with SLs. The proposed approach allows an on-line support to SL annotation, by ...
doi:10.1007/978-3-319-27863-6_27
fatcat:qyr23t7y2fh7nlhvqmnzgl47nu
Human Action Recognition Using Improved Salient Dense Trajectories
2016
Computational Intelligence and Neuroscience
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
In this paper, we present a more effective approach of video representation using improved salient dense trajectories: first, detecting the motion salient region and extracting the dense trajectories by ...
Human action recognition in videos is a topic of active research in computer vision. Dense trajectory (DT) features were shown to be efficient for representing videos in state-of-the-art approaches. ...
We first extract the motion salient region in videos. ...
doi:10.1155/2016/6750459
pmid:27293425
pmcid:PMC4886085
fatcat:g67kevkmkvdzxngamtivdregae
Action Recognition in Realistic Sports Videos
[chapter]
2014
Advances in Computer Vision and Pattern Recognition
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
We study several recent methods for action localization which have shown promising results on sports videos. ...
To provide further details about the existing action recognition methods in this area, we decompose the action recognition framework into three main steps of feature extraction, dictionary learning to ...
The majority of existing frameworks for action recognition consist of three main steps: feature extraction, dictionary learning to form a representation for a video based on the extracted features, and ...
doi:10.1007/978-3-319-09396-3_9
fatcat:q5kjcsnp2zb7fo5j4wwkjel5re
Unsupervised human activity analysis for intelligent mobile robots
2019
Artificial Intelligence
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
In this thesis an approach for unsupervised learning of activities implemented on an autonomous mobile robot is presented. ...
Finally, we present methods for learning such human activity models in an incremental and continuous setting using variational inference methods to update the activity distribution online. ...
Pixel-based abstraction This abstraction method relies on pixel-based information extracted from images such as colour, texture or gradients. ...
doi:10.1016/j.artint.2018.12.005
fatcat:vq56rrsuojfq3kzr3ip3tj4d74
Trajectory clustering for motion pattern extraction in aerial videos
2014
2014 IEEE International Conference on Image Processing (ICIP)
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2016; you can also visit the original URL.
The file type is application/pdf.
We present an end-to-end approach for trajectory clustering from aerial videos that enables the extraction of motion patterns in urban scenes. ...
Then clustering is performed based on statistics from the Discrete Wavelet Transform coefficients extracted from the trajectories. ...
This paper presents an end-to-end approach for trajectory clustering for motion pattern extraction in aerial videos. ...
doi:10.1109/icip.2014.7025203
dblp:conf/icip/NawazCR14
fatcat:jmjcoxr3xrhm5eto6uf2tw6g5q
Unsupervised Learning of Long-Term Motion Dynamics for Videos
2017
2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
We argue that in order for the decoder to reconstruct these sequences, the encoder must learn a robust video representation that captures long-term motion dependencies and spatial-temporal relations. ...
Given a pair of images from a video clip, our framework learns to predict the long-term 3D motions. ...
Next, we specially thank Juan Carlos Niebles, Serena Yeung, Kenji Hata, Yuliang Zou, and Lyne Tchapmi for their helpful feedback. ...
doi:10.1109/cvpr.2017.751
dblp:conf/cvpr/LuoPHAF17
fatcat:mnk4ejnkcreg5edgogrmoq6nuy
Learning Temporal Regularity in Video Sequences
2016
2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2016; you can also visit the original URL.
The file type is application/pdf.
We approach this problem by learning a generative model for regular motion patterns (termed as regularity) using multiple sources with very limited supervision. ...
We evaluate our methods in both qualitative and quantitative ways -showing the learned regularity of videos in various aspects and demonstrating competitive performance on anomaly detection datasets as ...
Most video based anomaly detection approaches involve a local feature extraction step followed by learning a model on training video. ...
doi:10.1109/cvpr.2016.86
dblp:conf/cvpr/0003CNRD16
fatcat:z4gq5mndhrcrbmitar2ldywfvq
Towards Good Practices for Action Video Encoding
2014
2014 IEEE Conference on Computer Vision and Pattern Recognition
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2014; you can also visit the original URL.
The file type is application/pdf.
We empirically evaluated various VLAD improvement technologies to determine good practices in VLAD-based video encoding. ...
Furthermore, we propose an interpretation that VLAD is a maximum entropy linear feature learning process. ...
Thus, Table 3 indicates that on average, more than 15% code words are missing in any single video-a fact that carries useful side information for categorizing a video's action type. ...
doi:10.1109/cvpr.2014.330
dblp:conf/cvpr/WuZL14
fatcat:6xy4uu5nizbubdtdc3dcodrmau
Learning to Manipulate Tools by Aligning Simulation to Video Demonstration
[article]
2021
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
For this we combine reinforcement learning with an optimization procedure to find a control policy and the placement of the robot based on the tool motion in the aligned environment. ...
Second, we describe an imitation learning approach that focuses on the trajectory of the tool rather than the motion of the human. ...
sand and the target box) based on the trajectory extracted from the video; (ii) we sample the simulation parameters from the constructed distribution, (iii) we follow the extracted trajectory in simulated ...
arXiv:2111.03088v1
fatcat:2i6sdoddyrgqtagoyfqqdmat44
Sports Video Analysis: Semantics Extraction, Editorial Content Creation and Adaptation
2009
Journal of Multimedia
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
In this paper, we summarize our research achievement on semantics extraction and automatic editorial content creation and adaptation in sports video analysis. ...
We first propose a generic multi-layer and multi-modal framework for sports video analysis. ...
On the server side, the highlights of the sports video were extracted based on replay detection. ...
doi:10.4304/jmm.4.2.69-79
fatcat:xytusontr5cyxlxpyqgljnhkqu
Video Activity Recognition: State-of-the-Art
2019
Sensors
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
In the area of robotics, the tasks of autonomous navigation or social interaction could also take advantage of the knowledge extracted from live video recording. ...
The aim of this paper is to survey the state-of-the-art techniques for video activity recognition while at the same time mentioning other techniques used for the same task that the research community has ...
One of the main techniques used for activity recognition is computer vision, namely video-based activity recognition. Visual video features provide basic information for video events or actions. ...
doi:10.3390/s19143160
fatcat:ore5paemmbfxzjimsvnnezgwwi
Efficient Analysis of Traffic Intersection Scenes by Employing Traffic Phase Information
2019
Iranian Journal of Electrical and Electronic Engineering
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Using side information on traffic phases, the semantic of motion patterns from traffic intersection scenes can be learned more effectively. ...
The learning is performed based on optical flow features extracted from training video clips, and applying them to supervised topic models such as MedLDA and MedSTC. ...
Based on such auxiliary information, we have formulated the problem of traffic motion pattern extraction and abnormality detection under supervised topic modeling framework. ...
doaj:5d2e4449c10a45fd895a32ab55d8570f
fatcat:ckqvaduvx5fdjfskhc3rmz4cui
Regularity Learning via Explicit Distribution Modeling for Skeletal Video Anomaly Detection
[article]
2021
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Other Versions
These two modules are then integrated into a unified framework for pose regularity learning, which is referred to as Motion Prior Regularity Learner (MoPRL). ...
Anomaly detection in surveillance videos is challenging and important for ensuring public security. ...
Specifically, we use the tools [12, 36] to obtain the pose trajectories as in [25] on ShanghaiTech. While for the Corridor dataset, we extract pose trajectories with tools [3, 7] as in [30] . ...
arXiv:2112.03649v2
fatcat:wgdridft3zaenls7kts5badtbq
« Previous
Showing results 1 — 15 out of 11,380 results