CN111882581B - 一种深度特征关联的多目标跟踪方法 - Google Patents
一种深度特征关联的多目标跟踪方法 Download PDFInfo
- Publication number
- CN111882581B CN111882581B CN202010705694.4A CN202010705694A CN111882581B CN 111882581 B CN111882581 B CN 111882581B CN 202010705694 A CN202010705694 A CN 202010705694A CN 111882581 B CN111882581 B CN 111882581B
- Authority
- CN
- China
- Prior art keywords
- target
- network
- matrix
- video frame
- loss
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 56
- 239000011159 matrix material Substances 0.000 claims abstract description 76
- 238000004364 calculation method Methods 0.000 claims abstract description 18
- 238000004458 analytical method Methods 0.000 claims abstract description 6
- 238000007781 pre-processing Methods 0.000 claims abstract description 6
- 238000001514 detection method Methods 0.000 claims description 21
- 238000012545 processing Methods 0.000 claims description 20
- 238000000605 extraction Methods 0.000 claims description 17
- 230000008569 process Effects 0.000 claims description 17
- 230000008859 change Effects 0.000 claims description 6
- 230000006835 compression Effects 0.000 claims description 5
- 238000007906 compression Methods 0.000 claims description 5
- 238000009499 grossing Methods 0.000 claims description 5
- 101000642315 Homo sapiens Spermatogenesis-associated protein 17 Proteins 0.000 claims description 3
- 102100036408 Spermatogenesis-associated protein 17 Human genes 0.000 claims description 3
- 230000003321 amplification Effects 0.000 claims description 3
- 238000003199 nucleic acid amplification method Methods 0.000 claims description 3
- 230000009467 reduction Effects 0.000 claims description 3
- 238000012360 testing method Methods 0.000 claims description 3
- 101100129500 Caenorhabditis elegans max-2 gene Proteins 0.000 claims 1
- 238000012549 training Methods 0.000 abstract description 3
- 230000006870 function Effects 0.000 description 9
- 230000008901 benefit Effects 0.000 description 7
- 238000013459 approach Methods 0.000 description 4
- 230000009286 beneficial effect Effects 0.000 description 4
- 238000010586 diagram Methods 0.000 description 4
- 238000013135 deep learning Methods 0.000 description 3
- 238000010219 correlation analysis Methods 0.000 description 2
- 230000005284 excitation Effects 0.000 description 2
- 238000001914 filtration Methods 0.000 description 2
- 230000006872 improvement Effects 0.000 description 2
- 230000014759 maintenance of location Effects 0.000 description 2
- 239000000203 mixture Substances 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000011160 research Methods 0.000 description 2
- 238000012098 association analyses Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000018109 developmental process Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 239000000284 extract Substances 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 230000011218 segmentation Effects 0.000 description 1
- 230000001502 supplementing effect Effects 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/20—Analysis of motion
- G06T7/246—Analysis of motion using feature-based methods, e.g. the tracking of corners or segments
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
- G06N3/045—Combinations of networks
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/60—Analysis of geometric attributes
- G06T7/66—Analysis of geometric attributes of image moments or centre of gravity
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10016—Video; Image sequence
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20081—Training; Learning
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20084—Artificial neural networks [ANN]
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- General Health & Medical Sciences (AREA)
- General Engineering & Computer Science (AREA)
- Biophysics (AREA)
- Computational Linguistics (AREA)
- Data Mining & Analysis (AREA)
- Evolutionary Computation (AREA)
- Artificial Intelligence (AREA)
- Molecular Biology (AREA)
- Computing Systems (AREA)
- Biomedical Technology (AREA)
- Life Sciences & Earth Sciences (AREA)
- Mathematical Physics (AREA)
- Software Systems (AREA)
- Health & Medical Sciences (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Multimedia (AREA)
- Geometry (AREA)
- Image Analysis (AREA)
Abstract
Description
Claims (5)
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202010705694.4A CN111882581B (zh) | 2020-07-21 | 2020-07-21 | 一种深度特征关联的多目标跟踪方法 |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202010705694.4A CN111882581B (zh) | 2020-07-21 | 2020-07-21 | 一种深度特征关联的多目标跟踪方法 |
Publications (2)
Publication Number | Publication Date |
---|---|
CN111882581A CN111882581A (zh) | 2020-11-03 |
CN111882581B true CN111882581B (zh) | 2022-10-28 |
Family
ID=73156317
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN202010705694.4A Active CN111882581B (zh) | 2020-07-21 | 2020-07-21 | 一种深度特征关联的多目标跟踪方法 |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN111882581B (zh) |
Families Citing this family (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN112330718B (zh) * | 2020-11-12 | 2022-08-23 | 重庆邮电大学 | 一种基于cnn的三级信息融合视觉目标跟踪方法 |
CN113343795B (zh) * | 2021-05-24 | 2024-04-26 | 广州智慧城市发展研究院 | 一种目标关联视频追踪处理方法 |
CN113762231B (zh) * | 2021-11-10 | 2022-03-22 | 中电科新型智慧城市研究院有限公司 | 端对端的多行人姿态跟踪方法、装置及电子设备 |
Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN108764063A (zh) * | 2018-05-07 | 2018-11-06 | 华中科技大学 | 一种基于特征金字塔的遥感影像时敏目标识别***及方法 |
CN110084124A (zh) * | 2019-03-28 | 2019-08-02 | 北京大学 | 基于特征金字塔网络的特征增强目标检测方法 |
CN110348445A (zh) * | 2019-06-06 | 2019-10-18 | 华中科技大学 | 一种融合空洞卷积和边缘信息的实例分割方法 |
CN111291759A (zh) * | 2020-01-17 | 2020-06-16 | 北京三快在线科技有限公司 | 文字检测方法、装置、电子设备及存储介质 |
CN111325279A (zh) * | 2020-02-26 | 2020-06-23 | 福州大学 | 一种融合视觉关系的行人与随身敏感物品跟踪方法 |
-
2020
- 2020-07-21 CN CN202010705694.4A patent/CN111882581B/zh active Active
Patent Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN108764063A (zh) * | 2018-05-07 | 2018-11-06 | 华中科技大学 | 一种基于特征金字塔的遥感影像时敏目标识别***及方法 |
CN110084124A (zh) * | 2019-03-28 | 2019-08-02 | 北京大学 | 基于特征金字塔网络的特征增强目标检测方法 |
CN110348445A (zh) * | 2019-06-06 | 2019-10-18 | 华中科技大学 | 一种融合空洞卷积和边缘信息的实例分割方法 |
CN111291759A (zh) * | 2020-01-17 | 2020-06-16 | 北京三快在线科技有限公司 | 文字检测方法、装置、电子设备及存储介质 |
CN111325279A (zh) * | 2020-02-26 | 2020-06-23 | 福州大学 | 一种融合视觉关系的行人与随身敏感物品跟踪方法 |
Non-Patent Citations (1)
Title |
---|
"Deep Affinity Network for Multiple Object Tracking";ShiJie Sun et al.;《arxiv》;20190716;第1-15页 * |
Also Published As
Publication number | Publication date |
---|---|
CN111882581A (zh) | 2020-11-03 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN111882581B (zh) | 一种深度特征关联的多目标跟踪方法 | |
CN113240691B (zh) | 一种基于u型网络的医学图像分割方法 | |
CN111260661B (zh) | 一种基于神经网络技术的视觉语义slam***及方法 | |
CN110827312B (zh) | 一种基于协同视觉注意力神经网络的学习方法 | |
CN113744311A (zh) | 基于全连接注意力模块的孪生神经网络运动目标跟踪方法 | |
CN112767478B (zh) | 一种基于表观指导的六自由度位姿估计方法 | |
CN111652081A (zh) | 一种基于光流特征融合的视频语义分割方法 | |
CN112651423A (zh) | 一种智能视觉*** | |
CN111797841A (zh) | 一种基于深度残差网络的视觉显著性检测方法 | |
CN116129289A (zh) | 一种注意力边缘交互的光学遥感图像显著性目标检测方法 | |
CN114612456B (zh) | 一种基于深度学习的钢坯自动语义分割识别方法 | |
CN112785626A (zh) | 一种基于多尺度特征融合的孪生网络小目标跟踪方法 | |
CN106529441A (zh) | 基于模糊边界分片的深度动作图人体行为识别方法 | |
CN113361475A (zh) | 一种基于多阶段特征融合信息复用的多光谱行人检测方法 | |
Wu et al. | Scene completeness-aware lidar depth completion for driving scenario | |
CN112069943A (zh) | 基于自顶向下框架的在线多人姿态估计与跟踪方法 | |
CN112115786A (zh) | 基于注意力U-net的单目视觉里程计方法 | |
CN114155273B (zh) | 一种结合历史轨迹信息的视频图像单目标跟踪方法 | |
CN116051950A (zh) | 跨层次跨模态双注意力融合的三流rgb-d显著性目标检测 | |
CN115512263A (zh) | 一种面向高空坠物的动态视觉监测方法及装置 | |
CN114693951A (zh) | 一种基于全局上下文信息探索的rgb-d显著性目标检测方法 | |
Zhu et al. | A Pose Estimation Method in Dynamic Scene with Yolov5, Mask R-CNN and ORB-SLAM2 | |
Tian et al. | Lightweight dual-task networks for crowd counting in aerial images | |
CN116486203B (zh) | 一种基于孪生网络和在线模板更新的单目标跟踪方法 | |
Guo et al. | Multi-Layer Fusion 3D Object Detection via Lidar Point Cloud and Camera Image |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
GR01 | Patent grant | ||
GR01 | Patent grant | ||
TR01 | Transfer of patent right | ||
TR01 | Transfer of patent right |
Effective date of registration: 20231215 Address after: 509 Kangrui Times Square, Keyuan Business Building, 39 Huarong Road, Gaofeng Community, Dalang Street, Longhua District, Shenzhen, Guangdong Province, 518000 Patentee after: Shenzhen lizhuan Technology Transfer Center Co.,Ltd. Address before: 266061 Qingdao University of Science & Technology, 99 Songling Road, Laoshan District, Qingdao, Shandong Patentee before: QINGDAO University OF SCIENCE AND TECHNOLOGY Effective date of registration: 20231215 Address after: No. 30316, 3rd Floor, Acceleration Building, Jiangdong E-commerce Industrial Park, No. 86 Qiongshan Avenue, Lingshan Town, Meilan District, Haikou City, Hainan Province, 570100 Patentee after: Hangxing Technology (Hainan) Co.,Ltd. Patentee after: Liang Guoxing Address before: 509 Kangrui Times Square, Keyuan Business Building, 39 Huarong Road, Gaofeng Community, Dalang Street, Longhua District, Shenzhen, Guangdong Province, 518000 Patentee before: Shenzhen lizhuan Technology Transfer Center Co.,Ltd. |
|
TR01 | Transfer of patent right | ||
TR01 | Transfer of patent right |
Effective date of registration: 20240205 Address after: Room 801, 7th Floor, Building 3, No. 128 South Fourth Ring West Road, Fengtai District, Beijing, 100000 Patentee after: BEIJING ZHONGKE HANGXING TECHNOLOGY Co.,Ltd. Country or region after: China Address before: No. 30316, 3rd Floor, Acceleration Building, Jiangdong E-commerce Industrial Park, No. 86 Qiongshan Avenue, Lingshan Town, Meilan District, Haikou City, Hainan Province, 570100 Patentee before: Hangxing Technology (Hainan) Co.,Ltd. Country or region before: China Patentee before: Liang Guoxing |