2021 Seminar Memo 2nd

# 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

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