13,045 Hits in 5.8 sec

Video-based Person Re-identification with Accumulative Motion Context [article]

Hao Liu, Zequn Jie, Karlekar Jayashree, Meibin Qi, Jianguo Jiang, Shuicheng Yan, Jiashi Feng
2017 arXiv   pre-print
context for video based person re-identification, validating our motivation evidently.  ...  Video based person re-identification plays a central role in realistic security and video surveillance.  ...  As video-based person re-identification involves recognizing a person from a sequence, accumulating the motion context information of each frame at each instant would be helpful to improve the performance  ... 
arXiv:1701.00193v2 fatcat:suxkybkj6nfynigcpwf5nnoeti

Vision Meets Wireless Positioning: Effective Person Re-identification with Recurrent Context Propagation [article]

Yiheng Liu, Wengang Zhou, Mao Xi, Sanjing Shen, Houqiang Li
2020 arXiv   pre-print
In this work, we approach person re-identification with the sensing data from both vision and wireless positioning.  ...  Existing person re-identification methods rely on the visual sensor to capture the pedestrians.  ...  For video-based person re-identification, many efforts are devoted to modeling the temporal clues along with the video frames.  ... 
arXiv:2008.04146v2 fatcat:bfgodxur3rasbclqsks76rwiey

Security and Surveillance [chapter]

Shaogang Gong, Chen Change Loy, Tao Xiang
2011 Visual Analysis of Humans  
This endeavour is intensified further by the need for understanding a massive quantity of video data, with the aim to comprehend multiple entities not only within a single image but also over time across  ...  multiple video frames for understanding their spatio-temporal relations.  ...  Visual context is also beneficial for resolving ambiguities from inter-camera tracking or person re-identification. For instance, Zheng et al.  ... 
doi:10.1007/978-0-85729-997-0_23 fatcat:lodvka4hu5debd7wiovexhca3u

Context-Aware Hypergraph Modeling for Re-identification and Summarization

Santhoshkumar Sunderrajan, B. S. Manjunath
2016 IEEE transactions on multimedia  
Also, the proposed algorithm is compared with the state of the art person re-identification algorithms on the VIPeR dataset [1].  ...  We consider the problem of person re-identification and tracking, and propose a novel clothing context-aware color extraction method that is robust to such changes.  ...  Furthermore, the proposed clothing context-aware person re-identification algorithm is compared with the state-of-the-art person re-identification algorithms in VIPeR dataset.  ... 
doi:10.1109/tmm.2015.2496139 fatcat:vpnool2wfzdgvdhppf53jagx2y

Person Re-Identification Using Group Information

Alina Bialkowski, Patrick Lucey, Xinyu Wei, Sridha Sridharan
2013 2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA)  
We demonstrate how this improves performance of person re-identification in a sports environment over appearance based-features.  ...  After first observing a person, the task of person re-identification involves recognising an individual at different locations across a network of cameras at a later time.  ...  Dataset To evaluate person re-identification using group context, we use team sports video data.  ... 
doi:10.1109/dicta.2013.6691512 dblp:conf/dicta/BialkowskiLWS13 fatcat:qxcrbzif2nbelhjsxnrmly3ea4

Image-to-Video Person Re-Identification by Reusing Cross-modal Embeddings [article]

Zhongwei Xie, Lin Li, Xian Zhong, Luo Zhong
2018 arXiv   pre-print
Image-to-video person re-identification identifies a target person by a probe image from quantities of pedestrian videos captured by non-overlapping cameras.  ...  The experimental results demonstrate the effectiveness of our framework on narrowing down the gap between heterogeneous data and obtaining observable improvement in image-to-video person re-identification  ...  Although more information can be obtained from videos, image-to-video re-identification shares the same common challenges with image-based and video-based person reidentification(e.g. similar appearance  ... 
arXiv:1810.03989v2 fatcat:q3vxzvnukfg25c2nill7y5it2m

Online Identification of Primary Social Groups [chapter]

Dimitra Matsiki, Anastasios Dimou, Petros Daras
2014 Lecture Notes in Computer Science  
In addition to the widely known criteria used in the literature for group identification, we present a novel one, which exploits the motion pattern of the trajectories.  ...  Experiments were conducted to provide evidence of the effectiveness of the proposed method with promising results.  ...  The predictions made are based on prior accumulated trajectories from the scene, exploiting context awareness.  ... 
doi:10.1007/978-3-319-04117-9_7 fatcat:cp5pmb7i2bcbnb4nx5v7547cqy

Where-and-When to Look: Deep Siamese Attention Networks for Video-based Person Re-identification [article]

Lin Wu, Yang Wang, Junbin Gao, Xue Li
2018 arXiv   pre-print
Video-based person re-identification (re-id) is a central application in surveillance systems with significant concern in security.  ...  There are two steps crucial to person re-id, namely discriminative feature learning and metric learning.  ...  DEEP SIAMESE ATTENTION NETWORKS FOR VIDEO-BASED PERSON RE-IDENTIFICATION In this section, we introduce attention based deep Siamese networks for video-based person re-id.  ... 
arXiv:1808.01911v2 fatcat:hl64uomz4vfwpihbmelosrtkdi

Person identification from streaming surveillance video using mid-level features from joint action-pose distribution

Binu M. Nair, Vijayan K. Asari, Robert P. Loce, Eli Saber
2015 Video Surveillance and Transportation Imaging Applications 2015  
We propose a real time person identification algorithm for surveillance based scenarios from low-resolution streaming video, based on mid-level features extracted from the joint distribution of various  ...  We demonstrate that these mid-level features captures the variation in the action performed with respect to an individual and can be used to distinguish one person from the next.  ...  These mid-level features are considered to be unique with respect to each individual and is fed to an SVM 13 based classification framework for person identification.  ... 
doi:10.1117/12.2083423 fatcat:q3r7rqa5snffpanwvnaqcmbxzm

Video Person Re-Identification using Learned Clip Similarity Aggregation

Neeraj Matiyali, Gaurav Sharma
2020 2020 IEEE Winter Conference on Applications of Computer Vision (WACV)  
We address the challenging task of video-based person re-identification.  ...  We also introduce the use of 3D CNNs for video-based re-identification and show their effectiveness by performing equivalent to previous works, which use optical flow in addition to RGB, while using RGB  ...  , remain largely unexplored for the task of video-based person re-identification.  ... 
doi:10.1109/wacv45572.2020.9093510 dblp:conf/wacv/MatiyaliS20 fatcat:gaafr7v3vjbshcr4oshood6dhm

Clip-Level Feature Aggregation: A Key Factor for Video-Based Person Re-identification [chapter]

Chengjin Lyu, Patrick Heyer-Wollenberg, Ljiljana Platisa, Bart Goossens, Peter Veelaert, Wilfried Philips
2020 Lecture Notes in Computer Science  
In the task of video-based person re-identification, features of persons in the query and gallery sets are compared to search the best match.  ...  AAS makes use of all frames in a video sequence to generate a better representation of a person, while RFU investigates how batch normalization operation influences feature representations in person reidentification  ...  [17] built a network which can accumulate motion context from adjacent frames by with the help of RNN.  ... 
doi:10.1007/978-3-030-40605-9_16 fatcat:y4owqk4n4rhfzbp3zqzjk77yh4

GLAMR: Global Occlusion-Aware Human Mesh Recovery with Dynamic Cameras [article]

Ye Yuan, Umar Iqbal, Pavlo Molchanov, Kris Kitani, Jan Kautz
2022 arXiv   pre-print
We present an approach for 3D global human mesh recovery from monocular videos recorded with dynamic cameras.  ...  To achieve this, we first propose a deep generative motion infiller, which autoregressively infills the body motions of occluded humans based on visible motions.  ...  In Stage I, we preprocess the video with multi-object tracking, re-identification and human mesh recovery to extract each person's occluded motion Q i in the camera coordinates.  ... 
arXiv:2112.01524v2 fatcat:f3kfqkmzqzdzjhjtrel43ktjtm

Video Person Re-Identification using Learned Clip Similarity Aggregation [article]

Neeraj Matiyali, Gaurav Sharma
2019 arXiv   pre-print
We address the challenging task of video-based person re-identification.  ...  We also introduce the use of 3D CNNs for video-based re-identification and show their effectiveness by performing equivalent to previous works, which use optical flow in addition to RGB, while using RGB  ...  remain largely unexplored for the task of video based person re-identification.  ... 
arXiv:1910.08055v1 fatcat:ydjtlv5nwvcm3kre5wnl33l3by

Efficient multi-camera vehicle detection, tracking, and identification in a tunnel surveillance application

Reyes Rios-Cabrera, Tinne Tuytelaars, Luc Van Gool
2012 Computer Vision and Image Understanding  
This Haar-features based 'tracking-by-identification' yields surprisingly good results on standard datasets, without the need to update the model online.  ...  The general multi-camera framework is validated using three tunnel surveillance videos.  ...  In terms of multi-camera re-identification some work has been done in the context of multi-camera person tracking.  ... 
doi:10.1016/j.cviu.2012.02.006 fatcat:yib6ibeg5faqvficbeti2qyhsy

Relation-Guided Spatial Attention and Temporal Refinement for Video-Based Person Re-Identification

Xingze Li, Wengang Zhou, Yun Zhou, Houqiang Li
Compared with image-based person re-identification, video-based person re-identification is characterized by a much richer context, which raises the significance of identifying informative regions and  ...  Video-based person re-identification has received considerable attention in recent years due to its significant application in video surveillance.  ...  Related Works Video-based Person Re-Identification.  ... 
doi:10.1609/aaai.v34i07.6807 fatcat:nudv3a5byvhvpb2pm5rra7kzte
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