I-Corps: Automated Attendance Check by Using Smartphone Cameras
I-Corps:使用智能手机摄像头自动考勤
基本信息
- 批准号:1521289
- 负责人:
- 金额:$ 5万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2015
- 资助国家:美国
- 起止时间:2015-01-15 至 2016-06-30
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Checking attendance in scenarios such as classrooms commonly needs an instructor to recognize each student one by one by reading the names on a roster or ask students to sign up the attendance sheet. However, this traditional method faces two problems: reading students' names may occupy minutes of lecture time when the number of students is large and letting students to sign up an attendance sheet is prone to be cheated since they can sign their own names and their classmates' names who are absent in the class; it is not a desirable task for instructors to calculate the total attendance of every student in a semester by going through every attendance sheet manually. This I-Corps team proposes an efficient and accurate way to accomplish this task. By taking videos of student faces in classrooms using Smartphone cameras, the team proposes a unified framework of visual face detection, tracking and recognition algorithms to recognize multi-faces in the video simultaneously.The proposed system has the following steps: instructors install the proposed App on their own Smartphones; in the first class, instructors use the Smartphone cameras to take a short-period video of student faces in the classroom. The application will automatically build a face dataset for the course and the instructor only needs to identify them for the first class; in the remaining classes, instructors take videos of each class and the application will do automated attendance check. The proposed Smartphone App will perform multi-object tracking to associate detected faces (including false positives) into face tracklets (each tracklet contains multiple instances of the same individual with variations in pose, illumination etc.) and then the face instances in each face tracklet are clustered into a small number of clusters, achieving sparse face representation with less redundancy.
在教室等场景中检查出勤率通常需要教师通过阅读花名册上的名字来逐个识别每个学生,或者要求学生在出勤表上签名。然而,这种传统的方法面临两个问题:当学生人数较多时,阅读学生的名字可能会占用几分钟的讲课时间,并且让学生在考勤表上签名容易被欺骗,因为他们可以在自己的名字和缺席的同学的名字上签名;教师若要计算每名学生在一个学期内的总出勤率,并不理想。这个I-Corps团队提出了一个有效和准确的方法来完成这项任务。通过使用智能手机摄像头在教室中拍摄学生面部视频,该团队提出了一个统一的视觉面部检测,跟踪和识别算法框架,以同时识别视频中的多张人脸。拟议的系统有以下步骤:教师在自己的智能手机上安装拟议的应用程序;在第一堂课上,教师使用智能手机摄像头在教室里拍摄学生面部的短时间视频。该应用程序将自动为课程构建人脸数据集,教师只需在第一堂课上识别它们;在其余课程中,教师将拍摄每堂课的视频,应用程序将自动进行考勤。申报的智能手机应用程序将执行多对象跟踪,以将检测到的面部(包括误报)关联到面部轨迹片段(每个轨迹片段包含同一个人的多个实例,姿态、照明等各不相同)。然后将每个人脸轨迹片段中的人脸实例聚类为少量的簇,从而实现具有较少冗余的稀疏人脸表示。
项目成果
期刊论文数量(0)
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科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Zhaozheng Yin其他文献
Semi-supervised Domain Adaptive Medical Image Segmentation through Consistency Regularized Disentangled Contrastive Learning
通过一致性正则化解缠对比学习进行半监督领域自适应医学图像分割
- DOI:
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2023 - 期刊:
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Spatial Attention Mechanism for Weakly Supervised Fire and Traffic Accident Scene Classification
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2019 - 期刊:
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M. Moniruzzaman;Zhaozheng Yin;Ruwen Qin - 通讯作者:
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A gaze-driven manufacturing assembly assistant system with integrated step recognition, repetition analysis, and real-time feedback
一个具有集成步骤识别、重复分析和实时反馈功能的基于注视驱动的制造装配辅助系统
- DOI:
10.1016/j.engappai.2025.110076 - 发表时间:
2025-03-15 - 期刊:
- 影响因子:8.000
- 作者:
Haodong Chen;Niloofar Zendehdel;Ming C. Leu;Zhaozheng Yin - 通讯作者:
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Co-restoring Multimodal Microscopy Images
共同恢复多模态显微图像
- DOI:
10.1007/978-3-319-24574-4_29 - 发表时间:
2015 - 期刊:
- 影响因子:0
- 作者:
Mingzhong Li;Zhaozheng Yin - 通讯作者:
Zhaozheng Yin
Freeway Travel Time Estimation using Existing Fixed Traffic Sensors – A ComputerVision-Based Vehicle Matching Approach Report # MATC-MS & T : 296 Final Report
使用现有固定交通传感器进行高速公路旅行时间估计 - 基于计算机视觉的车辆匹配方法报告 MATC-MS & T:296 最终报告
- DOI:
- 发表时间:
2015 - 期刊:
- 影响因子:0
- 作者:
Zhaozheng Yin - 通讯作者:
Zhaozheng Yin
Zhaozheng Yin的其他文献
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{{ truncateString('Zhaozheng Yin', 18)}}的其他基金
Collaborative Research: An Integrated, Proactive, and Ubiquitous Prosthetic Care Robot for People with Lower Limb Amputation: Sensing, Device Designing, and Control
合作研究:针对下肢截肢患者的集成、主动、无处不在的假肢护理机器人:传感、设备设计和控制
- 批准号:
2246673 - 财政年份:2023
- 资助金额:
$ 5万 - 项目类别:
Standard Grant
FW-HTF-RM: Collaborative Research: Assistive Intelligence for Cooperative Robot and Inspector Survey of Infrastructure Systems (AI-CRISIS)
FW-HTF-RM:协作研究:协作机器人辅助智能和基础设施系统检查员调查 (AI-CRISIS)
- 批准号:
2025929 - 财政年份:2020
- 资助金额:
$ 5万 - 项目类别:
Standard Grant
NRI: INT: COLLAB: Manufacturing USA: Intelligent Human-Robot Collaboration for Smart Factory
NRI:INT:COLLAB:美国制造:智能工厂的智能人机协作
- 批准号:
1954548 - 财政年份:2019
- 资助金额:
$ 5万 - 项目类别:
Standard Grant
CAREER: Microscopy Image Analysis to Aid Biological Discovery: Optics, Algorithms, and Community
职业:显微镜图像分析有助于生物发现:光学、算法和社区
- 批准号:
2019967 - 财政年份:2019
- 资助金额:
$ 5万 - 项目类别:
Standard Grant
NRI: INT: COLLAB: Manufacturing USA: Intelligent Human-Robot Collaboration for Smart Factory
NRI:INT:COLLAB:美国制造:智能工厂的智能人机协作
- 批准号:
1830479 - 财政年份:2018
- 资助金额:
$ 5万 - 项目类别:
Standard Grant
CAREER: Microscopy Image Analysis to Aid Biological Discovery: Optics, Algorithms, and Community
职业:显微镜图像分析有助于生物发现:光学、算法和社区
- 批准号:
1351049 - 财政年份:2014
- 资助金额:
$ 5万 - 项目类别:
Standard Grant
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