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学者姓名：陈锋
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Abstract ：
Detection-based tracking is one of the main methods of multi-object tracking. It can achieve good tracking performance when using excellent detectors but it may associate wrong targets when facing overlapping and low-confidence detections. To address this issue, this article proposes a novel multi-object tracker (SCTracker) by exploiting shape constraint and confidence. In the data association stage, an intersection of union (IoU) distance with shape constraints is developed to calculate the cost matrix between tracks and detections, which can reduce the track of the wrong target with the similar position but inconsistent shape. Moreover, the detection confidence is calculated in the update stage of the Kalman filter to improve the track performance with the inaccurate detection result. Experimental results on the MOT 17 dataset show that the proposed SCTracker can improve the tracking performance of multi-object tracking when compared with the state-of-the-art methods.
Keyword ：
Deep learning Deep learning distance measurement distance measurement motion estimation motion estimation object tracking object tracking
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| GB/T 7714 | Mao, Huan , Chen, Yulin , Li, Zongtan et al. SCTracker: Multi-Object Tracking With Shape and Confidence Constraints [J]. | IEEE SENSORS JOURNAL , 2024 , 24 (3) : 3123-3130 . |
| MLA | Mao, Huan et al. "SCTracker: Multi-Object Tracking With Shape and Confidence Constraints" . | IEEE SENSORS JOURNAL 24 . 3 (2024) : 3123-3130 . |
| APA | Mao, Huan , Chen, Yulin , Li, Zongtan , Chen, Pingping , Chen, Feng . SCTracker: Multi-Object Tracking With Shape and Confidence Constraints . | IEEE SENSORS JOURNAL , 2024 , 24 (3) , 3123-3130 . |
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Anomaly detection is represented as an unsupervised learning to identify deviated images from normal images. In general, there are two main challenges of anomaly detection tasks, i.e., the class imbalance and the unexpectedness of anomalies. In this paper, we propose a multiresolution feature guidance method based on Transformer named GTrans for unsupervised anomaly detection and localization. In GTrans, an Anomaly Guided Network (AGN) pre-trained on ImageNet is developed to provide surrogate labels for features and tokens. Under the tacit knowledge guidance of the AGN, the anomaly detection network named Trans utilizes Transformer to effectively establish a relationship between features with multiresolution, enhancing the ability of the Trans in fitting the normal data manifold. Due to the strong generalization ability of AGN, GTrans locates anomalies by comparing the differences in spatial distance and direction of multi-scale features extracted from the AGN and the Trans. Our experiments demonstrate that the proposed GTrans achieves state-of-the-art performance in both detection and localization on the MVTec AD dataset. GTrans achieves image-level and pixel-level anomaly detection AUROC scores of 99.0% and 97.9% on the MVTec AD dataset, respectively.
Keyword ：
Anomaly detection Anomaly detection Deep learning Deep learning Knowledge distillation Knowledge distillation Transformer Transformer
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| GB/T 7714 | Yan, Shuting , Chen, Pingping , Chen, Honghui et al. Multiresolution feature guidance based transformer for anomaly detection [J]. | APPLIED INTELLIGENCE , 2024 , 54 (2) : 1831-1846 . |
| MLA | Yan, Shuting et al. "Multiresolution feature guidance based transformer for anomaly detection" . | APPLIED INTELLIGENCE 54 . 2 (2024) : 1831-1846 . |
| APA | Yan, Shuting , Chen, Pingping , Chen, Honghui , Mao, Huan , Chen, Feng , Lin, Zhijian . Multiresolution feature guidance based transformer for anomaly detection . | APPLIED INTELLIGENCE , 2024 , 54 (2) , 1831-1846 . |
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随着远程监控和人工智能的融合发展,传统的码率优化算法并不适用于现阶段的移动监控网络场景.在机器视觉应用场景中,相对于传统码率优化算法只关注视频的质量,机器更关注于视频所表达的语义信息.以5G路侧摄像头远程智能检测为应用场景,提出一种基于视频语义的码率优化算法,在有限的码率传输范围内最大化目标检测准确率.具体地,该算法引入视频语义任务模型,将目标检测作为语义任务.分析目标比特与语义之间的特征关系,建立复杂度与运动区域结合的新权重来分配目标比特,使目标检测准确率达到最大化.实验结果表明,相较于HM16.23所使用的帧级树编码单元(Coding Tree Unit,CTU)层码率控制算法,所提算法不仅能够节省码率而且更符合无线远程监控的目标检测需求.在测试环境下平均提升了 1.4％的目标检测准确率,最高能够提升2.5％的目标检测准确率.
Keyword ：
人工智能 人工智能 机器视觉 机器视觉 目标检测 目标检测 视频语义 视频语义
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| GB/T 7714 | 黄发仁 , 柯捷铭 , 郑楚飞 et al. 基于视频语义的码率控制算法 [J]. | 无线电工程 , 2024 , 54 (8) : 1890-1899 . |
| MLA | 黄发仁 et al. "基于视频语义的码率控制算法" . | 无线电工程 54 . 8 (2024) : 1890-1899 . |
| APA | 黄发仁 , 柯捷铭 , 郑楚飞 , 周简心 , 张森林 , 陈锋 . 基于视频语义的码率控制算法 . | 无线电工程 , 2024 , 54 (8) , 1890-1899 . |
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In autonomous driving, the fusion of multiple sensors is considered essential to improve the accuracy and safety of 3D object detection. Currently, a fusion scheme combining low-cost cameras with highly robust radars can counteract the performance degradation caused by harsh environments. In this paper, we propose the IRBEVF-Q model, which mainly consists of BEV (Bird's Eye View) fusion coding module and an object decoder module.The BEV fusion coding module solves the problem of unified representation of different modal information by fusing the image and radar features through 3D spatial reference points as a medium. The query in the object decoder, as a core component, plays an important role in detection. In this paper, Heat Map-Guided Query Initialization (HGQI) and Dynamic Position Encoding (DPE) are proposed in query construction to increase the a priori information of the query. The Auxiliary Noise Query (ANQ) then helps to stabilize the matching. The experimental results demonstrate that the proposed fusion model IRBEVF-Q achieves an NDS of 0.575 and a mAP of 0.476 on the nuScenes test set. Compared to recent state-of-the-art methods, our model shows significant advantages, thus indicating that our approach contributes to improving detection accuracy.
Keyword ：
3D object detection 3D object detection attention mechanism attention mechanism multimodal fusion multimodal fusion query optimization query optimization transformer transformer
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| GB/T 7714 | Cai, Ganlin , Chen, Feng , Guo, Ente . IRBEVF-Q: Optimization of Image-Radar Fusion Algorithm Based on Bird's Eye View Features [J]. | SENSORS , 2024 , 24 (14) . |
| MLA | Cai, Ganlin et al. "IRBEVF-Q: Optimization of Image-Radar Fusion Algorithm Based on Bird's Eye View Features" . | SENSORS 24 . 14 (2024) . |
| APA | Cai, Ganlin , Chen, Feng , Guo, Ente . IRBEVF-Q: Optimization of Image-Radar Fusion Algorithm Based on Bird's Eye View Features . | SENSORS , 2024 , 24 (14) . |
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Abstract ：
随着智能多媒体技术和人工智能技术的融合发展，目标检测已广泛应用于移动监控网络远程传输场景。为了提升视频的目标检测精度，提出一种针对目标检测的码率优化算法，在有限的码率范围内使得物体的检测准确率达到最大化。将目标检测作为视频语义任务，分析视频码率比特与目标检测之间的关系，建立目标比特分配模型，从而使目标检测准确率达到最大化。实验结果表明，所提算法不仅能节省视频码率，还能提升目标检测精度。
Keyword ：
人工智能 人工智能 目标检测 目标检测 视频语义 视频语义
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| GB/T 7714 | 黄发仁 , 陈锋 , 吴宜婷 et al. 基于目标检测的码率优化算法 [J]. | 电视技术 , 2024 , 48 (04) : 20-24 . |
| MLA | 黄发仁 et al. "基于目标检测的码率优化算法" . | 电视技术 48 . 04 (2024) : 20-24 . |
| APA | 黄发仁 , 陈锋 , 吴宜婷 , 林灿辉 . 基于目标检测的码率优化算法 . | 电视技术 , 2024 , 48 (04) , 20-24 . |
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The sudden surge of various applications poses great challenges to the computation capability of mobile devices.To address this issue,computation offloading to multi-access edge computing(MEC)was proposed as a promising paradigm.This paper studies partial computation offloading scenario by considering time delay and energy consumption,where the task can be splitted into several blocks and computed both in local devices and MEC,respectively.Since the formulated problem is a nonconvex problem,this paper proposes an ant colony-based algorithm to achieve the suboptimal solution.Specifically,the proposed method first establish a multi-user one-MEC scenario,in which user devices are able to offload some part of the task to MEC server.Then,it develops an ant colony-based algorithm to decide the offloading parts and allocation strategy of MEC resources to minimize system cost.Finally,simulation results show the effectiveness of the proposed algorithm in terms of system cost and demonstrate that it outperforms other existing methods.
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| GB/T 7714 | Wu Hongxin , Lin Zhijian , Chen Pingping et al. Joint partial computation offloading and resource allocation in MEC-enable networks [J]. | 中国邮电高校学报（英文版） , 2023 , 30 (1) : 80-86 . |
| MLA | Wu Hongxin et al. "Joint partial computation offloading and resource allocation in MEC-enable networks" . | 中国邮电高校学报（英文版） 30 . 1 (2023) : 80-86 . |
| APA | Wu Hongxin , Lin Zhijian , Chen Pingping , Chen Feng . Joint partial computation offloading and resource allocation in MEC-enable networks . | 中国邮电高校学报（英文版） , 2023 , 30 (1) , 80-86 . |
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针对5G网络中多路视频并发上行传输可能因I帧冲突导致网络拥塞的问题，本文建立了多源视频I帧碰撞概率模型，提出一种基于区分服务模型（DiffServ）的多源视频业务优先级循环排队转发流量整形机制，用于优化各路视频流I帧时隙及平滑多路视频码流。之后，对差额加权轮询（DWRR）、轮询（RR）、严格优先级队列（SPQ）调度算法与双速三色令牌桶（trTCM）流量监管级联策略下各队列时延与丢包率进行联合对比，实验结果表明DWRR+trTCM在上行速率受限的情况下能更好地保障业务优先级高的视频流时延及可靠性。
Keyword ：
业务优先级 业务优先级 服务质量 服务质量 流量整形 流量整形 视频传输 视频传输 队列调度 队列调度
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| GB/T 7714 | 王君 , 陈锋 , 张森林 et al. 多源视频优先级队列调度及流量整形方法研究 [J]. | 广播电视网络 , 2023 , 30 (04) : 50-55 . |
| MLA | 王君 et al. "多源视频优先级队列调度及流量整形方法研究" . | 广播电视网络 30 . 04 (2023) : 50-55 . |
| APA | 王君 , 陈锋 , 张森林 , 周简心 . 多源视频优先级队列调度及流量整形方法研究 . | 广播电视网络 , 2023 , 30 (04) , 50-55 . |
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为满足5G实时视频传输的可靠性和低时延需求,提出一种面向低时延实时视频前向纠错(Forward Error Correction,FEC)传输控制算法.该算法根据实时视频帧到达情况和当前网络状况,建模FEC编码、缓冲区数据包与端到端时延之间的关系,优化当前时间段FEC编码器的最佳参数.实验结果证明,该算法能够使得98％的视频数据时延控制在100 ms之内,相较于静态前向纠错机制,时延平均减少了30 ms,且用户平均接收视频数据的有效损失率降低约2％.
Keyword ：
前向纠错 前向纠错 端到端时延 端到端时延 视频传输 视频传输
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| GB/T 7714 | 杨梅 , 陈锋 , 高廷金 et al. 一种超低时延FEC实时视频编码算法 [J]. | 电视技术 , 2023 , 47 (3) : 13-16,22 . |
| MLA | 杨梅 et al. "一种超低时延FEC实时视频编码算法" . | 电视技术 47 . 3 (2023) : 13-16,22 . |
| APA | 杨梅 , 陈锋 , 高廷金 , 俞萍萍 . 一种超低时延FEC实时视频编码算法 . | 电视技术 , 2023 , 47 (3) , 13-16,22 . |
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The safety of autonomous driving is closely linked to accurate depth perception. With the continuous development of autonomous driving, depth completion has become one of the crucial methods in this field. However, current depth completion methods have major shortcomings in small objects. To solve this problem, this paper proposes an end-to-end architecture with adaptive spatial feature fusion by encoder-decoder (ASFF-ED) module for depth completion. The architecture is built on the basis of the network architecture proposed in this paper, and is able to extract depth information adaptively with different weights on the specified feature map, which effectively solves the problem of insufficient depth accuracy of small objects. At the same time, this paper also proposes a depth map visualization method with a semi-quantitative visualization, which makes the depth information more intuitive to display. Compared with the currently available depth map visualization methods, this method has stronger quantitative analysis and horizontal comparison ability. Through experiments of ablation study and comparison, the results show that the method proposed in this paper exhibits a lower root-mean-squared error (RMSE) and better small object detection performance on the KITTI dataset.
Keyword ：
autonomous driving autonomous driving computer vision computer vision depth completion depth completion image processing image processing multi-source information fusion for sensing multi-source information fusion for sensing
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| GB/T 7714 | Wang, Hantao , Guo, Ente , Chen, Feng et al. Depth Completion in Autonomous Driving: Adaptive Spatial Feature Fusion and Semi-Quantitative Visualization [J]. | APPLIED SCIENCES-BASEL , 2023 , 13 (17) . |
| MLA | Wang, Hantao et al. "Depth Completion in Autonomous Driving: Adaptive Spatial Feature Fusion and Semi-Quantitative Visualization" . | APPLIED SCIENCES-BASEL 13 . 17 (2023) . |
| APA | Wang, Hantao , Guo, Ente , Chen, Feng , Chen, Pingping . Depth Completion in Autonomous Driving: Adaptive Spatial Feature Fusion and Semi-Quantitative Visualization . | APPLIED SCIENCES-BASEL , 2023 , 13 (17) . |
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The sudden surge of various applications poses great challenges to the computation capability of mobile devices. To address this issue, computation offloading to multi-access edge computing (MEC) was proposed as a promising paradigm. This paper studies partial computation offloading scenario by considering time delay and energy consumption, where the task can be splitted into several blocks and computed both in local devices and MEC, respectively. Since the formulated problem is a nonconvex problem, this paper proposes an ant colony-based algorithm to achieve the suboptimal solution. Specifically, the proposed method first establish a multi-user one- MEC scenario, in which user devices are able to offload some part of the task to MEC server. Then, it develops an ant colony-based algorithm to decide the offloading parts and allocation strategy of MEC resources to minimize system cost. Finally, simulation results show the effectiveness of the proposed algorithm in terms of system cost and demonstrate that it outperforms other existing methods. © 2023, Beijing University of Posts and Telecommunications. All rights reserved.
Keyword ：
ant colony-based algorithm ant colony-based algorithm mobile edge computing mobile edge computing partial computation offloading partial computation offloading resource allocation resource allocation
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| GB/T 7714 | Hongxin, W. , Zhijian, L. , Pingping, C. et al. Joint partial computation offloading and resource allocation in MEC-enable networks [J]. | Journal of China Universities of Posts and Telecommunications , 2023 , 30 (1) : 80-86 . |
| MLA | Hongxin, W. et al. "Joint partial computation offloading and resource allocation in MEC-enable networks" . | Journal of China Universities of Posts and Telecommunications 30 . 1 (2023) : 80-86 . |
| APA | Hongxin, W. , Zhijian, L. , Pingping, C. , Feng, C. . Joint partial computation offloading and resource allocation in MEC-enable networks . | Journal of China Universities of Posts and Telecommunications , 2023 , 30 (1) , 80-86 . |
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