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Mitsunori Tada

Publications and source records attributed to Mitsunori Tada.

3 recordsLinked to original sources

Map-Mono-Ego: Map-Grounded Global Human Pose Estimation from Monocular Egocentric Video

Monocular egocentric human pose estimation is essential for ubiquitous activity monitoring. However, understanding the user's absolute location within the environment remains a challenge. Existing methods primarily focus on relative motion from an initial position, and tend not to account for the wearer's absolute location within an environment. Furthermore, inherent scale ambiguity in monocular vision leads to severe translational drift, limiting long-term tracking without specialized multi-sensor hardware. To address this, we propose MapMonoEgo, a novel framework achieving globally consistent human pose estimation solely from a monocular camera by leveraging a pre-scanned 3D point cloud. We also introduce AIST-Living dataset, a new dataset pairing egocentric video with ground-truth motion in a scanned environment. Experiments demonstrate that our approach significantly outperforms the state-of-the-art baseline, proving its utility for practical monitoring tasks without specialized hardware.

cs.CV

Development of fall prevention training device that can provide external disturbance to the ankle with pneumatic gel muscles (PGM) while walking

Although the average life expectancy in Japan has been increasing in recent years, the problem of the large gap between healthy life expectancy and average life expectancy is still unresolved. Among the factors that lead to the need for nursing care, injuries due to falls account for a certain percentage of the total. In this paper, we developed boots that can provide external disturbance to the ankle with pneumatic gel muscles (PGM) while walking. We experimented using an angular velocity and acceleration of the heel as evaluation indices to evaluate the effectiveness of fall prevention training using this device, which is smaller and more wearable than conventional devices. In this study, we confirmed that the developed system has enough training intensity to significantly affect the gait waveform.

cs.HC

Unsupervised Neural Motion Retargeting for Humanoid Teleoperation

This study proposes an approach to human-to-humanoid teleoperation using GAN-based online motion retargeting, which obviates the need for the construction of pairwise datasets to identify the relationship between the human and the humanoid kinematics. Consequently, it can be anticipated that our proposed teleoperation system will reduce the complexity and setup requirements typically associated with humanoid controllers, thereby facilitating the development of more accessible and intuitive teleoperation systems for users without robotics knowledge. The experiments demonstrated the efficacy of the proposed method in retargeting a range of upper-body human motions to humanoid, including a body jab motion and a basketball shoot motion. Moreover, the human-in-the-loop teleoperation performance was evaluated by measuring the end-effector position errors between the human and the retargeted humanoid motions. The results demonstrated that the error was comparable to those of conventional motion retargeting methods that require pairwise motion datasets. Finally, a box pick-and-place task was conducted to demonstrate the usability of the developed humanoid teleoperation system.

cs.RO