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32nd ACM International Conference on Multimedia, MM 2024

作者： Zhou, Yanshan Lai, Pingrui Yu, Jiaqi Xiong, Yingjie Yang, Hua Institute of Image Communication and Network Engineering Shanghai Jiao Tong University Shanghai China Shanghai Key Lab of Digital Media Processing and Transmission Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9798400706868

With global occurrences of crowd crushes and stampedes, dense crowd simulation has been drawing great attention. In this research, our goal is to simulate dense crowd motions under six classic motion patterns, more specifically, to generate subsequent motions of dense crowds from the given initial states. Since dense crowds share similarities with fluids, such as continuity and fluidity, one common approach for dense crowd simulation is to construct hydrodynamics-based models, which consider dense crowds as fluids, guide crowd motions with Navier-Stokes equations, and conduct dense crowd simulation by solving governing equations. Despite the proposal of these models, dense crowd simulation faces multiple challenges, including the difficulty of directly solving Navier-Stokes equations due to their nonlinear nature, the ignorance of distinctive crowd characteristics which fluids lack, and the gaps in the evaluation and validation of crowd simulation models. To address the above challenges, we build a hydrodynamic model, which captures the crowd physical properties (continuity, fluidity, etc.) with Navier-Stokes equations and reflects the crowd social properties (sociality, personality, etc.) with operators that describe crowd interactions and crowd-environment interactions. To tackle the computational problem, we propose to solve the governing equation based on Navier-Stokes equations using neural networks, and introduce the Hydrodynamics-Informed Neural Network (HINN) which preserves the structure of the governing equation in its network architecture. To facilitate the evaluation, we construct a new dense crowd motion video dataset called Dense Crowd Flow Dataset (DCFD), containing six classic motion patterns (line, curve, circle, cross, cluster and scatter) and 457 video clips, which can serve as the groundtruths for various objective metrics. Numerous experiments are conducted using HINN to simulate dense crowd motions under six motion patterns with video clips fro

关键词： Navier Stokes equations

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A NOVEL CROSS-LAYER STRATEGY OF VIDEO TRANSMISSION TO SOLVE PERFORMANCE ANOMALY IN MULTI-RATE IEEE 802.11 NETWORKS

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Journal of Electronics(China) 2011年第3期28卷 349-358页

作者： Tang Guijin Zhu Xiuchang Key Lab of Image Processing ＆ Communication Nanjing University of Posts and Telecommunications Nanjing 210003 China

When wireless hosts use different rates to transmit data in IEEE 802.11 networks, it will take on the state of performance anomaly which will severely decrease the throughputs of all the higher rate hosts. Hence, it is bad for video service transmission. Considering that video is very sensitive to packet delivery delay but can tolerate some packet losses, we propose a novel cross-layer scheme which takes these two characteristics into consideration. Firstly, the maximum number of retransmissions for a video Medium Access Control (MAC) frame is computed in MAC layer according to video frame rate requirement of application layer and current access delay of MAC layer. Secondly, within the margin of the tolerant Packet Loss Rate (PLR) of application layer, several video MAC frames are allowed to drop so that we can adaptively select the transmission rate as high as possible for the rest of video MAC frames in terms of current channel quality and the maximum number of retransmissions. Experiment results show that the proposed method can reduce the delay and jitter of video service and improve the throughputs of fast hosts. Therefore, it increases the quality of reconstructed video to a certain extent and relieves the performance anomaly of network effectively.

关键词： Multi-rate Video transmission IEEE 802.11 Performance anomaly Cross-layer

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Neonatal Pain Expression Recognition Based on LBP Features and Sparse Representation

Neonatal Pain Expression Recognition Based on LBP Features a...

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2015 World Conference on Control, Electronics and Electrical Engineering(WCEE 2015)

作者： Guanming Lu Mengying Chen Xiaonan Li Jiangsu Province Key Lab on Image Processing & Image Communication Nanjing University of Posts and Telecommunications Nanjing Children's Hospital Affiliated to Nanjing Medical University

Facial expressions are considered a reliable indicator in neonatal pain *** paper proposes a new neonatal pain expression recognition method,which utilizes the feature descriptors based on weighted Local Binary Pattern(LBP)and the classifier based on sparse ***,the normalized facial image is described using a feature vector,which is histogram sequence obtained by concatenating the weighted histograms of the LBP maps of all the local ***,the Principal Component Analysis(PCA)method is used to reduce the dimension of the feature ***,the classifier based on sparse representation is applied to classify test sample into four classes of facial expressions:calm,crying,moderate pain,severe *** objective of this study is to assist the clinicians in assessing neonatal pain by utilizing computer-based image analysis *** experimental results on neonate facial image database show the effectiveness of the proposed *** classification accuracy is up to 85.50%.

关键词： expression recognition,local binary pattern,sparse representation,neonate,pain expression.

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PRN: Psychology-Inspired Relation Network for Detecting Social Interaction Groups from Single images 32

PRN: Psychology-Inspired Relation Network for Detecting Soci...

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32nd British Machine Vision Conference, BMVC 2021

作者： Yu, Jiaqi Yang, Jinhai Yang, Hua Zhai, Guangtao Institute of Image Communication and Network Engineering Shanghai Jiao Tong University ChinaShanghai Key Lab of Digital Media Processing and Transmission Shanghai ChinaMoE Key Lab of Artificial Intelligence AI Institute Shanghai Jiao Tong University China

Detecting interaction groups is an essential task for understanding human behaviours and social activities. However, it is still challenging to identify social interactions and the resulting crowd groups using purely visual cues, especially from single images. Prior works either require additional statistics, such as interpersonal angles and kinaesthetic information, or simply deduce the group memberships with the similarity of individual actions. In this paper, we present the Psychology-inspired Relation Network (PRN) to comprehensively understand the static social scenes and effectively model the interaction relations between individuals. More concretely, stimulated by recent advances in social psychology, we first predict the keypoint heatmap from an image with the human bounding boxes as the visual representations of the key factors determining interaction groups: distance, orientation and postural openness. We then incorporate the personal and mutual influences together to compute the interaction strength matrix via self-attention, and finally utilise a perception to convert this matrix into dyadic interaction probability. Moreover, we devise two loss functions, the dyad loss to optimise the dyadic interaction probability and the group loss to enhance the distinguishability among different social groups. To evaluate the performance of PRN, we introduce a novel dataset containing various scenes with different crowd densities, by merging representative databases and relabeling the group labels. Our method achieves outstanding results on the proposed dataset. © 2021. The copyright of this document resides with its authors.

关键词： Computer vision

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Compressed video super-resolution reconstruction based on regularized algorithm

Compressed video super-resolution reconstruction based on re...

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International Conference on Signal processing Proceedings (ICSP)

作者： Xu Zhong-qiang Gan Zongliang Zhu Xiu-chang Information Industry Ministry and Jiangsu Province Key Laboratory of Image Processing & Image Communication Nanjing University of Posts and Telecommunications Nanjing China

Estimating high-resolution (HR) video from a sequence of low-resolution (LR) compressed observations is the focus of this paper. Based on the theory of regularization, this paper proposes a new form of regularized cost function to control the within-channel balance between received data and prior information, and a channel weight coefficient to control the cross-channel fidelity. The LR frames are adaptively weighted according to their reliability and the regularization parameter is simultaneously estimated for each channel with ameliorating artifacts in compressed video. An iterative gradient descent algorithm is utilized to reconstruction the HR video. Experimental results demonstrate that the proposed algorithm has an improvement in terms of both objective and subjective quality

关键词： Video compression image coding Iterative algorithms image resolution image reconstruction Cost function Discrete cosine transforms Quantization image storage Gallium nitride

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Evaluation of bodily-kinesthetic intelligence based on computer contextual method

Evaluation of bodily-kinesthetic intelligence based on compu...

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2013 International Conference on Sport Science and Computer Science (CCCS 2013)

作者： Qi Xia Wei Wang Jun Wang College of Education Science Nanjing Normal University Key Laboratory of Image Processing and Image Communication of Jiangsu Province Nanjing University of Posts and Telecommunications

There are two main types of tests to assess one's bodily-kinesthetic intelligence,which are writing tests and scenario ***,these two methods are subjective and time-consuming and not suitable for large-scale *** paper proposed a new assess method to assess bodily-kinesthetic intelligence based on the writing intelligence test *** method is designed with the computer virtual reality *** result shows the method can get better reliability and *** the evaluation process is easier to realize.

关键词： bodily-kinesthetic intelligence multiple intelligence computer contextual method

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A compressive sensing based mobile video communication system

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Sensors and Transducers 2013年第6期153卷 186-191页

作者： Wu, Minghu Li, Ran Zhou, Shangli School of Electrical and Electronic Engineering Hubei University of Technology Wu'han 430068 China Jiangsu Province Key Lab on Image Processing and Image Communication Nanjing University of Posts and Telecommunications Nanjing 210003 China

A compressive sensing (CS) based mobile video communication system is proposed to meet the requirement that video service needs low-complexity video encoder in the mobile internet. In this system, the mobile client uses CS based video encoder having low computational complexity and power, and then its output bit-stream is decoded using CS recovery algorithm in the fixed base station or network server. The decoded video signal is transformed again as bits by the traditional H.264/MPEG video encoder, and the central base station transmits them to mobile clients so as to realizing low-complexity video decoding. The simulation experiments show that the proposed CS based mobile video communication system has the better rate-distortion performance, and can ensure high quality video reconstruction at low measurement rates. © 2013 IFSA.

关键词： Compressed sensing

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Multi-agent middleware for the integration of mobile supply chain

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Journal of Computers 2011年第7期6卷 1469-1476页

作者： Zhao, Weidong Wu, Haifeng Dai, Weihui Li, Xuan Yu, Fei Xu, Chen School of Software Fudan University Shanghai China Jiangsu Provincial Key Lab of Image Processing and Image Communications Nanjing University of Posts and Telecommunications Nanjing China

With the development of mobile network and communication technology, traditional supply chain management is gradually updating to mobile supply chain management, and multi-agent technology has been considered as a very efficient method for supply chain management in mobile environment. After considering the characteristics and limitations of mobile supply chain, and according to the requirements in the manufacturing domain, this paper designs a multi-agent middleware for mobile supply chain management, aiming to solve integration problems and shield off network and terminal heterogeneity in mobile environment, which can achieve mobile supply chain dynamic integration and then improve the efficiency of supply chain management. Its feasibility and efficiency was demonstrated by experiments. © 2011 ACADEMY PUBLISHER.

关键词： Middleware

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Adaptive and Collaborative Multi-scale Alignment for Text-Based Person Search

Adaptive and Collaborative Multi-scale Alignment for Text-Ba...

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2023 IEEE International Conference on Visual communications and image processing, VCIP 2023

作者： Yang, Xinxin Pan, Renjie Yang, Hua Institute of Image Communication and Network Engineering Shanghai Jiao Tong University Shanghai Key Lab of Digital Media Processing and Transmission Shanghai China Shanghai Jiao Tong University China MoE Key Lab of Artificial Intelligence AI Institute China

ISBN: (纸本)9798350359855

Text-To-image person search is challenging due to the cross-scale correspondences and information inequality between modalities. Specifically, images and text are complexly linked at different scales and images are usually more informative and complete than text. It is crucial to establish semantic correlations between modalities and focus on task-relevant information in images. In this paper, we propose a novel Adaptive and Collaborative Multi-scale Alignment network (ACMA) for text-based person search that learns semantically consistent and information-Aligned multi-modal representations. Firstly, we introduce a novel joint embedding module that adaptively integrates features of different pixels and words, thereby extracting semantically consistent multi-modal features at different scales. Second, we design a cross-modal fusion feature-based auxiliary visual branch to guide the extraction of key visual features that are beneficial for cross-modal matching. Extensive experiments validate that ACMA outperforms the state-of-The-Art method. © 2023 IEEE.

关键词： Embeddings

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Joint DBF and SAO parallel filtering based on multithread load balancing

Joint DBF and SAO parallel filtering based on multithread lo...

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2020 International Symposium on Automation, Information and Computing, ISAIC 2020

作者： Ma, Hao Hu, Dong Li, Yi Jiangsu Province’s Key Lab of Image Procession and Image Communications Nanjing210003 China Education Ministry’s Key Lab of Broadband Wireless Communication and Sensor Network Technology Nanjing210003 China Education Ministry’s Engineering Research Center of Ubiquitous Network and Heath Service Nanjing University of Posts and Telecommunications Nanjing210003 China

This paper presents a joint parallel loop filtering algorithm based on multi-thread load balancing in HEVC decoding, which implements the parallel processing of deblocking filtering (DBF) and sample adaptive compensation (SAO). Because of the diversity of video, the texture of different regions in an image is also different, which leads to various CTU partition methods. Therefore, the number of the boundary to be filtered is greatly different, resulting the computation load among multiple threads unbalanced in parallel processing. To solve this problem, an area division scheme is proposed, which divides the image into multiple areas, and the number of boundaries to be filtered in each area is similar. Then, the mapping relationship table is used to allocate these areas to multiple threads for parallel processing, so as to achieve the load balancing among the filtering threads. Finally, the cache technology is used to combine DBF and SAO to reduce the delay between them and improve the overall parallelism of the loop filter. Experimental results show that the performance of the proposed load balancing joint filtering algorithm is 8.15% higher than the previous scheme. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Textures

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