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ADAPTIVE MOTION ESTIMATION ALGORITHM FOR CROWDED SCENES by KAJO, IBRAHIM

“…Lots of crowd motion estimation algorithms have been presented in the last years comprising pedestrian motion. …”
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Zero acceleration algorithm with state of motion identifier for position estimation of wheeled robot by Tan, Zhi Zhong

“…In this research, a state of motion identifier framework is proposed to apply a novel kinematic motion constraint to position estimation system. …”
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An adaptive block-based matching algorithm for crowd motion sequences by Kajo, I., Kamel, N., Malik, A.S.

“…Lots of crowd motion estimation algorithms have been presented in the last years comprising pedestrian motion. …”
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An adaptive block-based matching algorithm for crowd motion sequences by Kajo, I., Kamel, N., Malik, A.S.

“…Lots of crowd motion estimation algorithms have been presented in the last years comprising pedestrian motion. …”
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Non-pressurized magnetorheological damper controlled using fuzzy semi active damping force estimator (fSADE) by Saiful Anuar, Abu Bakar, Hishamuddin, Jamaluddin, Roslan, Abd Rahman, Pakharuddin, Mohd Samin, Ryosuke, Masuda, Hiromu, Hashimoto, Takeshi, Inaba

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An evaluation of optical flow algorithms for crowd analytics in surveillance system by Kajo, I., Malik, A.S., Kamel, N.

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REAL-TIME HORN-SCHUNCK OPTICAL FLOW HARDWARE ARCHITECTURE FOR HIGH ACCURACY MOTION ESTIMATION by RUZALI, RUZALI

“…The optical flow constraint equation of Horn-Schunck (OFCE-HS) is an algorithm used to compute motion estimation from the apparent motion of image sequences. …”
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Upper Limb Joint Angle Estimation Using Wearable IMUs and Personalized Calibration Algorithm by Rahman, Md. Mahmudur, Beng Gan, Kok, Abd Aziz, Noor Azah, Huong, , Audrey, You, Huay Woon

“…Multiple trials using the proposed algorithm estimated the elbow joint angle of the rigid body with a maximum RMSE of 0.46◦ Using the IMU manufacturer’s (WitMotion) algorithm (Kalman filter), the maximum RMSE was 1.97◦ For the fourth trial, joint angles were also calculated with external acceleration, and the RMSE was 0.996◦ In all cases, the joint angles were within therapeutic limits.…”
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Upper Limb Joint Angle Estimation Using Wearable IMUs and Personalized Calibration Algorithm by Rahman, Md. Mahmudur, Gan, Kok Beng, Abd Aziz, Noor Azah, Huong, Audrey, Woon You, Huay

“…Multiple trials using the proposed algorithm estimated the elbow joint angle of the rigid body with a maximum RMSE of 0.46◦ Using the IMU manufacturer’s (WitMotion) algorithm (Kalman filter), the maximum RMSE was 1.97◦ For the fourth trial, joint angles were also calculated with external acceleration, and the RMSE was 0.996◦ In all cases, the joint angles were within therapeutic limits.…”
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Upper Limb Joint Angle Estimation Using Wearable IMUs and Personalized Calibration Algorithm by Md. Mahmudur Rahman, Md. Mahmudur Rahman, Kok Beng Gan, Kok Beng Gan, Abd Aziz, Noor Azah, Audrey Huong, Audrey Huong, Huay Woon You, Huay Woon You

“…Using the IMU manufacturer’s (WitMotion) algorithm (Kalman filter), the maximum RMSE was 1.97◦ . …”
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Upper Limb Joint Angle Estimation Using Wearable IMUs and Personalized Calibration Algorithm by Md. Mahmudur Rahman, Md. Mahmudur Rahman, Kok Beng Gan, Kok Beng Gan, Abd Aziz, Noor Azah, Audrey Huong, Audrey Huong, Huay Woon You, Huay Woon You

“…Using the IMU manufacturer’s (WitMotion) algorithm (Kalman filter), the maximum RMSE was 1.97◦ . …”
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Upper Limb Joint Angle Estimation Using Wearable IMUs and Personalized Calibration Algorithm by Rahman, Md. Mahmudur, Kok Beng Gan, Kok Beng Gan, Abd Aziz, Noor Azah, Audrey Huong, Audrey Huong, Huay Woon You, Huay Woon You

“…Using the IMU manufacturer’s (WitMotion) algorithm (Kalman filter), the maximum RMSE was 1.97◦ . …”
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Upper Limb Joint Angle Estimation Using Wearable IMUs and Personalized Calibration Algorithm by Rahman, Md. Mahmudur, Kok Beng Gan, Kok Beng Gan, Abd Aziz, Noor Azah, Huong, Audrey, Huay Woon You, Huay Woon You

“…Using the IMU manufacturer’s (WitMotion) algorithm (Kalman filter), the maximum RMSE was 1.97◦ . …”
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Upper Limb Joint Angle Estimation Using Wearable IMUs and Personalized Calibration Algorithm by Rahman, Md. Mahmudur, Kok Beng Gan, Kok Beng Gan, Abd Aziz, Noor Azah, Audrey Huong, Audrey Huong, Huay Woon You, Huay Woon You

“…Using the IMU manufacturer’s (WitMotion) algorithm (Kalman filter), the maximum RMSE was 1.97◦ . …”
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Upper Limb Joint Angle Estimation Using Wearable IMUs and Personalized Calibration Algorithm by Md. Mahmudur Rahman, Md. Mahmudur Rahman, Kok Beng Gan, Kok Beng Gan, Abd Aziz, Noor Azah, Audrey Huong, Audrey Huong, Huay Woon You, Huay Woon You

“…Multiple trials using the proposed algorithm estimated the elbow joint angle of the rigid body with a maximum RMSE of 0.46◦ Using the IMU manufacturer’s (WitMotion) algorithm (Kalman filter), the maximum RMSE was 1.97◦ . …”
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Upper Limb Joint Angle Estimation Using Wearable IMUs and Personalized Calibration Algorithm by Md. Mahmudur Rahman, Md. Mahmudur Rahman, Kok Beng Gan, Kok Beng Gan, Noor Azah Abd Aziz, Noor Azah Abd Aziz, Audrey Huong, Audrey Huong, Huay Woon You, Huay Woon You

“…Using the IMU manufacturer’s (WitMotion) algorithm (Kalman filter), the maximum RMSE was 1.97◦ . …”
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Motion estimation on homogenous surface for around view monitoring system by Hanizam, Syahirah, Nik Hashim, Nik Nur Wahidah, Zainal Abidin, Zulkifli, Mohd Zaki, Hasan Firdaus, Abdul Rahman, Hasbullah, Mahamud, Nurul Hidayah

“…We propose to develop two ultra-wide-angle cameras located on the front and rear vehicle integrated with the motion estimation (ME) algorithm to produce a parking bird eye view and forward/backward trajectory lines. …”
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Around view monitoring system with motion estimation in ADAS application by Rasdi, Muhammad Hannan Fathi, Nik Hashim, Nik Nur Wahidah, Hanizam, Syahirah

“…Here, proposed an AVM system that will integrate with the motion estimation algorithm to produce a good result. …”
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SLOW DRIFT MOTIONS IDENTIFICATION OF FLOATING STRUCTURES USING TIME-VARYING INPUT -OUTPUT MODELS by YAZID, EDWAR

“…The first step is presenting the backward estimator and combined forward-backward estimator instead of the only forward estimator in the original input-output models; the second step is reformulating the input-output models into a state-space model so that the Kalman Smoother (KS) adaptive filter can be used to estimate the model coefficients; the third step is optimization of KS parameters using evolutionary computing algorithms such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and Artificial Bee Colony (ABC) to form the PSO-KS, GA-KS and ABC-KS as estimation methods.…”
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Speed and Angle Estimation of Mobile Terminal in Distributed Antenna Systems by Jeoti , Varun

“…Furthermore, the angle of mobile motion is more helpful for developing these algorithms and also in the mobile unit (MU) tracking systems. …”
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