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Hierarchical Visual attention Model for Saliency Detection Inspired by Avian visual Pathways

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IEEE/CAA Journal of Automatica Sinica 2019年第2期6卷 540-552页

作者： Xiaohua Wang Haibin Duan the State Key Laboratory of Virtual Reality Technology and Systems School of Automation Science and Electrical Engineering Beihang University the State Key Laboratory of Virtual Reality Technology and Systems School of Automation Science and Electrical EngineeringBeihang University the Peng Cheng Laboratory

Visual attention is a mechanism that enables the visual system to detect potentially important objects in complex environment. Most computational Visual attention models are designed with inspirations from mammalian visual systems.However, electrophysiological and behavioral evidences indicate that avian species are animals with high visual capability that can process complex information accurately in real time. Therefore,the visual system of the avian species, especially the nuclei related to the Visual attention mechanism, are investigated in this paper. Afterwards, a hierarchical Visual attention model is proposed for saliency detection. The optic tectum neuron responses are computed and the self-information is used to compute primary saliency maps in the first hierarchy. The "winner-takeall" network in the tecto-isthmal projection is simulated and final saliency maps are estimated with the regularized random walks ranking in the second hierarchy. Comparison results verify that the proposed model, which can define the focus of attention accurately, outperforms several state-of-the-art models.This study provides insights into the relationship between the Visual attention mechanism and the avian visual pathways. The computational Visual attention model may reveal the underlying neural mechanism of the nuclei for biological Visual attention.

关键词： Avian visual pathways bio-inspired saliency detection Visual attention

Wayfinding design in transportation architecture-are saliency models or designer Visual attention a good predictor of passenger Visual attention?

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Frontiers of Architectural Research 2020年第4期9卷 726-738页

作者： Ran Xu Haishan Xia Mei Tian School of Architecture and Design Beijing Jiaotons UniversityBeijing 100044China School of Computer and Information Technology Beijing Jiaotons UniversityBeijing 100044China

In transportation architecture,wayfinding quality is a crucial factor for determining transfer efficiency and level of service.When developing architectural design concepts,designers often employ their Visual attention to imagine where passengers will look.A saliency model is a software program that can predict human Visual attention.This research examined whether a saliency model or designer Visual attention is a good predictor of passenger Visual attention during wayfinding in side transportation architecture.Using a remote eye-tracking system,the eye-movements of 29 participants watching 100 still images depicting different indoor seenes of transportation architecture were recorded and transformed into saliency maps to illustrate participants'Visual attention.Participants were categorized as either"designers"or"laypeople"based on their architectural design expertise.Similarities were compared among the"designers'"Visual attention,saliency model predictions,and"laypeople's"Visual attention.The results showed that while the"designers'"Visual attention was the best predictor of that of"laypeople",followed by saliency models,a single desig ner's visual attend on was not a good predictor.The divergence in Visual attention highlights the limitation of designers in predicting passenger wayfinding behavior and implies that integrating a saliency model in practice can be beneficial for wayfinding design.

关键词： Tran sportation architecture design Passenger wayfinding Path choice Visual attention Eye fixation

基于视觉注意的移动机器人环境3D建模（英文）

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自动化学报 2017年第7期43卷 1248-1256页

作者：郭炳华戴宏跃李中华 Department of Electrical and Information Engineering Zhaoqing University School of Data and Computer Science Sun Yat-sen University

Human Visual attention is highly selective.The artificial vision system that imitates this mechanism increases the efficiency,intelligence,and robustness of mobile robots in environment modeling.This paper presents a 3-D modeling method based on Visual attention for mobile robots.This method uses the distance–potential gradient as motion contrast and combines the visual features extracted from the scene with a mean shift segment algorithm to detect conspicuous objects in the surrounding environment.This method takes the saliency of objects as priori information,uses Bayes’ theorem to fuse sensor modeling and grid priori modeling,and uses the projection method to create and update the 3-D environment modeling.The results of the experiments and performance evaluation illustrate the capabilities of our approach in generating accurate 3-D maps.

关键词： 3-D Mapping grid model mobile robots Visual attention

Temporal continuity of Visual attention for future gaze prediction in immersive virtual reality

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Virtual Reality & Intelligent Hardware 2020年第2期2卷 142-152页

作者： Zhiming HU Sheng LI Meng GAI Department of Computer Science and Technology School of Electronic Engineering and Computer SciencePeking UniversityBeijing 100871China Beijing Engineering Technology Research Center of Virtual Simulation and visualization Peking UniversityBeijing 100871China

Background Eye tracking te chnology is receiving increased attention in the field of virtual reality.Specifically,future gaze prediction is crucial in pre-computation for many applications such as gaze-contingent rendering,advertisement placement,and content-based design.To explore future gaze prediction,it is necessary to analyze the temporal continuity of Visual attention in immersive virtual reality.Methods In this paper,the concept of temporal continuity of Visual attention is presented.Subsequently,an autocorrelation function method is proposed to evaluate the temporal continuity.Thereafter,the temporal continuity is analyzed in both free-viewing and task-oriented conditions.Results Specifically,in free-viewing conditions,the analysis of a free-viewing gaze dataset indicates that the temporal continuity performs well only within a short time interval.A task-oriented game scene condition was created and conducted to collect users'gaze data.An analysis of the collected gaze data finds the temporal continuity has a similar performance with that of the free-viewing conditions.Temporal continuity can be applied to future gaze prediction and if it is good,users'current gaze positions can be directly utilized to predict their gaze positions in the future.Conclusions The current gaze's future prediction performances are further evaluated in both free-viewing and task-oriented conditions and discover that the current gaze can be efficiently applied to the task of short-term future gaze prediction.The task of long-term gaze prediction still remains to be explored.

关键词： Temporal continuity Visual attention Autocorrelation analysis Gaze prediction Virtual reality

Hand gesture tracking algorithm based on Visual attention

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Journal of Beijing Institute of Technology 2016年第4期25卷 491-501页

作者：冯志全徐涛吕娜唐好魁蒋彦梁丽伟 School of Information Science and Engineering University of JinanJinan 250022China Shandong Provincial Key Laboratory of Network-Based Intelligent Computing Jinan 250022China

In the majority of the interaction process, the operator often focuses on the tracked 3D hand gesture model at the ＂interaction points＂ in the collision detectionscene, such as ＂grasp＂ and ＂release＂ and objects in the scene, without paying attention to the tracked 3D hand gesture model in the total procedure. Thus in this paper, a Visual attention distribution model of operator in the ＂grasp＂, ＂translation＂, ＂release＂ and other basic operation procedures is first studied and a 3D hand gesture tracking algorithm based on this distribution model is proposed. Utilizing the algorithm, in the period with a low degree of Visual attention, a pre-stored 3D hand gesture animation can be used to directly visualise a 3D hand gesture model in the interactive scene; in the time period with a high degree of Visual attention, an existing ＂frame-by-frame tracking＂ approach can be adopted to obtain a 3D gesture model. The results demonstrate that the proposed method can achieve real-time tracking of 3D hand gestures with an effective improvement on the efficiency, fluency, and availability of 3D hand gesture interaction.

关键词： Visual attention 3D hand gesture tracking hand gesture interaction

A coarse-to-fine image registration method based on Visual attention model

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Science China(Information Sciences) 2014年第12期57卷 122-131页

作者： FENG Jing MA Long BI FuKun ZHANG XueJing CHEN He School of Information and Electronics Beijing Institute of Technology College of Information Engineering North China University of Technology College of Information Technology Beijing Union University

Image registration is fundamental and crucial to remote sensing.However getting highly accurate registration performance automatically and fast for large-field images consistently is a challenge.As a work around to this problem,we propose a new image registration concept based on Visual attention in this paper.This concept employs the advantages of feature-based or area-based methods to improve the precision and efficiency of image registration.The key concept of proposed integrated scheme is to make optimum use of the highly prominent details in the full scene by means of Visual attention computational mechanism.To testify the validation,comparisons with other classical methods are carried out on real-world images.The experimental results show that the proposed method can effectively perform on multi-view/multi-temporal remote sensing images with outstanding precision and time saving performance.

关键词： remote sensing image registration Visual attention similarity measure partial correlation coarseto-fine process

Visual attention based model for target detection in large-field images

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Journal of Systems Engineering and Electronics 2011年第1期22卷 150-156页

作者： Lining Gao Fukun Bi Jian Yang Department of Electronic Engineering Tsinghua University Beijing 100084 P. R. China School of Information and Electronics Beijing Institute of Technology Beijing 100081 E R. China

It is of great significance to rapidly detect targets in large-field remote sensing images,with limited computation resources.Employing relative achievements of Visual attention in perception psychology,this paper proposes a hierarchical attention based model for target detection.Specifically,at the preattention stage,before getting salient regions,a fast computational approach is applied to build a saliency map.After that,the focus of attention（FOA） can be quickly obtained to indicate the salient objects.Then,at the attention stage,under the FOA guidance,the high-level visual features of the region of interest are extracted in parallel.Finally,at the post-attention stage,by integrating these parallel and independent visual attributes,a decision-template based classifier fusion strategy is proposed to discriminate the task-related targets from the other extracted salient objects.For comparison,experiments on ship detection are done for validating the effectiveness and feasibility of the proposed model.

关键词： target detection Visual attention salient region classifier fusion.

A Visual attention Model for Robot Object Tracking

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International Journal of Automation and computing 2010年第1期7卷 39-46页

作者： Jin-Kui Chu Rong-Hua Li Qing-Ying Li Hong-Qing Wang School of Mechanical Engineering, Dalian University of Technology, Dalian 116024, PRC School of Mechanical Engineering Dalian University of Technology Dalian PRC

Inspired by human behaviors, a robot object tracking model is proposed on the basis of Visual attention mechanism, which is fit for the theory of topological perception. The model integrates the image-driven, bottom-up attention and the object-driven, top-down attention, whereas the previous attention model has mostly focused on either the bottom-up or top-down attention. By the bottom-up component, the whole scene is segmented into the ground region and the salient regions. Guided by top-down strategy which is achieved by a topological graph, the object regions are separated from the salient regions. The salient regions except the object regions are the barrier regions. In order to estimate the model, a mobile robot platform is developed, on which some experiments are implemented. The experimental results indicate that processing an image with a resolution of 752 × 480 pixels takes less than 200 ms and the object regions are unabridged. The analysis obtained by comparing the proposed model with the existing model demonstrates that the proposed model has some advantages in robot object tracking in terms of speed and efficiency.

关键词： Object tracking Visual attention topological perception salient regions weighted similarity equation

A saliency model based on wavelet transform and Visual attention

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Science China(Information Sciences) 2010年第4期53卷 738-751页

作者： LI ZhiQiang, FANG Tao* & HUO Hong Institute of Image Processing and Pattern Recognition, Shanghai Jiaotong University, Shanghai 200240, China Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China

This paper presents a novel wavelet transform saliency model to detect salient objects. In this model, a saliency map is generated by combining orientation feature maps obtained from wavelet transform of different scale images derived from the same image. Then, the order map of a saliency map is obtained by using Fourier descriptor, which could be used as a guidance to process the most important objects. Experiments indicate that this saliency model is robust to noise and superior to other saliency models in the literature.

关键词： bottom-up attentional mechanism center-surround inhibition phenomenon Fourier descriptor top-down attentional mechanism Visual attention wavelet transform