---
# System prepended metadata

title: 2021 Seminar Memo 2nd
tags: [JLab]

---

# 2021 Seminar Memo 2nd

###### tags: `JLab`
[TOC]
#### 2022/01/12
G1(Lu):
* d8222104 Chenghong Lu
    * TDL 
        * do the additional exp.
        * revise the paper of TIM
    * Future work
        * verify the new program of the method (AI-enhenced KF)
        * full body IMU mocap implementation (less than 1 meter)

* d8232103 Wei Guo
    * TDL
        * get AoA from CSI using MUSIC alg.
        * buy NIC for exp.
    * some questions and comments
        * What does calibration mean and how is it done. Is there a reference.

* s1250021 Shunsei Yamagishi 
    * impl the eclipse calibration for M sensor
    * TDL
        * read PDR paper　（IPIN）
        * IPIN data for evl exp.
        * the  difinition of zero
        * detection accuracy of the zero speed point
        * error analysis for diff filter th
        * measurement the error rate for different paths
    * some questions and comments
        * RMSE
        * Magnetic calibration
        * dead reckoning
#### 12/2
G1(Lu):
* d8222104 Chenghong Lu
    * TDL 
        * do the additional exp.
        * revise the paper of TIM
    * Future work
        * verify the new program of the method (AI-enhenced KF)
        * full body IMU mocap implementation (less than 1 meter)

* d8232103 Wei Guo
    * TDL
        * get AoA from CSI using MUSIC alg.
        * buy NIC for exp.
    * some questions and comments
        * What does calibration mean and how is it done. Is there a reference.

* s1250021 Shunsei Yamagishi 
    * impl the eclipse calibration for M sensor
    * TDL
        * read PDR paper　（IPIN）
        * IPIN data for evl exp.
        * the  difinition of zero
        * detection accuracy of the zero speed point
        * error analysis for diff filter th
        * measurement the error rate for different paths
    * some questions and comments
        * In the results section of Experiment 1, a large part of it was stationary, so the results were good.
        * How to synchronize between systems.
        * How to get the true values.
        * In order to verify the results, do we need to use an optical system (vicon).
#### 11/17
G1(Lu):
* d8222104 Chenghong Lu
    * TDL 
        * do the additional exp.
        * revise the paper of TIM
    * Future work
        * verify the new program of the method (AI-enhenced KF)
        * full body IMU mocap implementation (less than 1 meter)

* d8232103 Wei Guo
    * TDL
        * get AoA from CSI using MUSIC alg.
        * buy NIC for exp.
    * some questions and comments
        * What does calibration mean and how is it done. Is there a reference.

* s1250021 Shunsei Yamagishi 
    * impl the eclipse calibration for M sensor
    * TDL
        * read PDR paper　（IPIN）
        * IPIN data for evl exp.
        * the  difinition of zero
        * detection accuracy of the zero speed point
        * error analysis for diff filter th
        * measurement the error rate for different paths
    * some questions and comments
        * In the results section of Experiment 1, a large part of it was stationary, so the results were good.
        * How to synchronize between systems.
        * How to get the true values.
        * In order to verify the results, do we need to use an optical system (vicon).
G2(Chen):
* m5242106 Hongbo Chen
    * respond the ICMI paper
    * tested the new idea
    * TDL
        * slide number
        * add units
        * clarify your contributions
        * what, why, how
* m5241146 Yuto Shoji
    * TDL 
        * exp. design (show me)
        * sys verify with self data
        * data collection for offline evaluation (CSI+IMU)
* m5242119 Yuting Tang 
    * extract the hand skeleton (MediaPipe)
    * TDL
        * try on the sign dataset
        * try with CNN or LSTM
        * read related works 
        * slide
* s1260244 Yuriya Nakamura
    * 
    * TDL 
        *  read paper (HAR, RGB-D, sign language)
        *  test ST-GCN on the sign dataset
* s1260223 Tsukasa Nagata 
    * 
    * TDL
        * impliment the test system with GA on Nikke data
        * summary the related works into slides
* m5251121 Kinemuchi Shun
    * PCA/kNN
    * TDL 
        * try PCA/kNN/DT sample code on some data
        * slide
        * 整形
* m5251122 KOZAKAI Misaki
    * 
    * TDL
        * ###given a reading out degree from the sensor, how to predict the degree of each joint
            * regression problem
        * Kosign data segmentation with SSD(Show me)
* m5251125 Xiaoyang Liu
    * read the paper
    * TDL
        * skeleton detection on the dolls and robots (to follow paper on Nature Method)

G3(Miyada):
* m5251129 Daisuke Miyada
    * 
    * TDL
        * BNN (case study: Rock-paper-scissors)
        * Wi-Fi-->Unity
* m5231147 Tsubasa Endo
    * input coordination data of desktop to Unity
    * TDL 
        * slide
            * related work (features list up)
            * experiment design
        * PoC system implementation

* s1260196 Taisei Kodama
    * get emotion
    * TDL
        * Impliment Mr.Wang system
        
* s1260141 Yuta Nomi
    * 
    * TDL
        * learn how to control motor car in Unity
        * data collection with Joy-con with python, recognition (kNN) with python, visualization with Unity 
* m5251123 Haicui Li
    * finished the HCII
    * TDL
        * study on the toothbrush research
        * slide



S3:
* s1270162  NAGAMINE Haru
    * send me the paper (cat activity)
    * TDL
        * open dataset for the cat
            * kaggle
            * from the paper
        * how to collect the cat HAR data
        * learn the python
        * HAR (human activity recognition)
* s1270199  SATO Kazuma
    * hand mocap with Glove (sensor/camera)
    * discuss with me 
* s1270093  SAKASAI Ryoma
    * HAR
* s1270129  IWAMOTO Tsubasa
    * read the related paper 電磁石
    * keywoard "haptic", **"indirect"**
    * unity vr keyboard
    * MYO  
#### 11/10
G1(Lu):
* d8222104 Chenghong Lu
    * TDL 
        * do the additional exp.
        * revise the paper of TIM
    * Future work
        * verify the new program of the method (AI-enhenced KF)
        * full body IMU mocap implementation (less than 1 meter)

* d8232103 Wei Guo
    * TDL
        * AoA to body coordination
        * clear noise of CSI
        * get AoA from CSI
        * check the open data set for the exp
* s1250021 Shunsei Yamagishi 
    * impl the eclipse calibration for M sensor
    * TDL
        * read PDR paper　（IPIN）
        * IPIN data for evl exp.
        * the  difinition of zero
        * detection accuracy of the zero speed point
        * error analysis for diff filter th
        * measurement the error rate for different paths
    * some questions and comments
        * In the results section of Experiment 1, a large part of it was stationary, so the results were good.
        * How to synchronize between systems.
        * How to get the true values.
        * In order to verify the results, do we need to use an optical system (vicon).
G2(Chen):
* m5242106 Hongbo Chen
    * respond the ICMI paper
    * tested the new idea
    * TDL
        * slide number
        * add units
        * clarify your contributions
        * what, why, how
* m5241146 Yuto Shoji
    * TDL 
        * exp. design (show me)
        * sys verify with self data
        * data collection for offline evaluation (CSI+IMU)
* m5242119 Yuting Tang 
    * extract the hand skeleton (MediaPipe)
    * TDL
        * try on the sign dataset
        * try with CNN or LSTM
        * read related works 
        * slide
* s1260244 Yuriya Nakamura
    * 
    * TDL 
        *  read paper (HAR, RGB-D, sign language)
        *  test ST-GCN on the sign dataset
* s1260223 Tsukasa Nagata 
    * 
    * TDL
        * impliment the test system with GA on Nikke data
        * summary the related works into slides
* m5251121 Kinemuchi Shun
    * PCA/kNN
    * TDL 
        * try PCA/kNN/DT sample code on some data
        * slide
        * 整形
* m5251122 KOZAKAI Misaki
    * 
    * TDL
        * ###given a reading out degree from the sensor, how to predict the degree of each joint
            * regression problem
        * Kosign data segmentation with SSD(Show me)
* m5251125 Xiaoyang Liu
    * read the paper
    * TDL
        * skeleton detection on the dolls and robots (to follow paper on Nature Method)

G3(Miyada):
* m5251129 Daisuke Miyada
    * 
    * TDL
        * BNN (case study: Rock-paper-scissors)
        * Wi-Fi-->Unity
* m5231147 Tsubasa Endo
    * input coordination data of desktop to Unity
    * TDL 
        * slide
            * related work (features list up)
            * experiment design
        * PoC system implementation

* s1260196 Taisei Kodama
    * get emotion
    * TDL
        * Impliment Mr.Wang system
        
* s1260141 Yuta Nomi
    * 
    * TDL
        * learn how to control motor car in Unity
        * data collection with Joy-con with python, recognition (kNN) with python, visualization with Unity 
* m5251123 Haicui Li
    * finished the HCII
    * TDL
        * study on the toothbrush research
        * slide



S3:
* s1270162  NAGAMINE Haru
    * send me the paper (cat activity)
    * TDL
        * open dataset for the cat
            * kaggle
            * from the paper
        * how to collect the cat HAR data
        * learn the python
        * HAR (human activity recognition)
* s1270199  SATO Kazuma
    * hand mocap with Glove (sensor/camera)
    * discuss with me 
* s1270093  SAKASAI Ryoma
    * HAR
* s1270129  IWAMOTO Tsubasa
    * read the related paper 電磁石
    * keywoard "haptic", **"indirect"**
    * unity vr keyboard
    * MYO  
