• ETRI Journal
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• v.39 no.2
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• pp.181-190
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• 2017

The movements of the human body are difficult to capture owing to the complexity of the three-dimensional skeleton model and occlusion problems. In this paper, we propose a motion capture system that tracks dynamic human motions in real time. Without using external markers, the proposed system adopts multiple depth sensors (Microsoft Kinect) to overcome the occlusion and body rotation problems. To combine the joint data retrieved from the multiple sensors, our calibration process samples a point cloud from depth images and unifies the coordinate systems in point clouds into a single coordinate system via the iterative closest point method. Using noisy skeletal data from sensors, a posture reconstruction method is introduced to estimate the optimal joint positions for consistent motion generation. Based on the high tracking accuracy of the proposed system, we demonstrate that our system is applicable to various motion-based training programs in dance and Taekwondo.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.283-286
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• 2002

This paper presents the straightness compensation system which is a device for improving the machining accuracy of ultra-precision machines by synchronizing the position of diamond tool tip with machine error motion. Sine it is actuated by piezoelectric actuator with highly nonlinear hysteresis characteristics, the feedback control schemes such as Proportional Integral(PI), are required and realized by measuring the displacements of diamond tool tip. for the better tracking performance, the controller was implemented using TMS320C32 32bit floating-point DSP which is fast so that the real-time control is possible. In addition, stand alone type DSP board was chosen fur the easy assembly into the ultra-precision machines. The experimental results show good command tracking performance and the motion error of the machine is satisfactorily compensated during the machining process.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.10a
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• pp.154-161
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• 1999

This paper presents a new approach to the design of adaptive control system using DSPs(TMS320C30) for robotic manipulators to achieve trajectory tracking by the joint angles. Digital signal processors are used in implementing real time adaptive control algorithms to provide an enhanced motion control for robotic manipulators. In the proposed control scheme, adaptation laws are derived from the improved Lyapunov second stability analysis method based on the adaptive model reference control theory. The adaptive controller consists of an adaptive feedforward controller, feedback controller, and PID type time-varying auxillary control elements. The proposed adaptive control scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Moreover, this scheme does not require an accurate dynamic modeling, nor values of manipulator parameters and payload. Performance of the adaptive controller is illustrated by simulation and experimental results for a SCARA robot.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1996.03a
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• pp.79-84
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• 1996

This paper presents a new approach to the design of adaptive control system using DSPs(TMS320C31) for robotic manipulators to achieve trajectory tracking by the joint angles. Digital signal processors are used in implementing real time adaptive control algorithms to provide an enhanced motion control for robotic manipulators. In the proposed control scheme, adaptation laws are derived from the improved Lyapunov second stability analysis method based on the adaptive model reference control theory. The adaptive controller consists of an adaptive feedforward controller, feedback controller, and PID type time-varying auxillary control elements. The proposed adaptive control scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Moreover, this scheme does not require an accurate dynamic modeling, nor values of manipulator parameters and payload. Performance of the adaptive controller is illustrated by simulation and experimental results for a SCARA robot.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.5 no.4
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• pp.26-37
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• 1996

This paper presents a new approach to the design of adaptive control system using DSPs(TMS320C30) for robotic manipulators to achieve trajectory tracking by the joint angles Digital signal processors are used in implementing real time adaptive control algorithms to provide an enhanced motion control for robotic manipulators. In the proposed control scheme adaptation laws are derived from the improved Lyapunov second stability analysis method based on the adaptive model reference control theory. The adaptive controller consists of an adaptive feedforward controller. feedback controller. and PID type time-varying auxiliary control elements. The proposed adaptive control scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Moreover, this scheme does not require a an accurate dynamic modeling, nor values of manipulator parameters and payload. Performance of the adaptive controller is illustrated by simulation and experimental results for a SCARA robot.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.6
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• pp.459-463
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• 2009

Background modeling and motion detection is the one of the most significant real time video processing technique. Until now, many researches are conducted into the topic but it still needs much time for robustness. It is more important when other algorithms are used together such as object tracking, classification or behavior understanding. In this paper, we propose efficient multi-modal background modeling methods which can be understood as simplified learning method of Gaussian mixture model. We present its validity using numerical methods and experimentally show detecting performance.

• Journal of Broadcast Engineering
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• v.20 no.3
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• pp.449-463
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• 2015

Video object tracking is important for variety of applications, such as security, video indexing and retrieval, video surveillance, communication, and compression. This paper proposes an object tracking method in HEVC bitstreams. Without pixel reconstruction, motion vector (MV) and size of prediction unit in the bitstream are employed in an Spatio-Temporal Markov Random Fields (ST-MRF) model which represents the spatial and temporal aspects of the object's motion. Coefficient-based object shape adjustment is proposed to solve the over-segmentation and the error propagation problems caused in other methods. In the experimental results, the proposed method provides on average precision of 86.4%, recall of 79.8% and F-measure of 81.1%. The proposed method achieves an F-measure improvement of up to 9% for over-segmented results in the other method even though it provides only average F-measure improvement of 0.2% with respect to the other method. The total processing time is 5.4ms per frame, allowing the algorithm to be applied in real-time applications.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.2 no.2
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• pp.120-133
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• 2008

This paper presents a novel approach for facial motion tracking and facial expression cloning to create a realistic facial animation of a 3D avatar. The exact head pose estimation and facial expression tracking are critical issues that must be solved when developing vision-based computer animation. In this paper, we deal with these two problems. The proposed approach consists of two phases: dynamic head pose estimation and facial expression cloning. The dynamic head pose estimation can robustly estimate a 3D head pose from input video images. Given an initial reference template of a face image and the corresponding 3D head pose, the full head motion is recovered by projecting a cylindrical head model onto the face image. It is possible to recover the head pose regardless of light variations and self-occlusion by updating the template dynamically. In the phase of synthesizing the facial expression, the variations of the major facial feature points of the face images are tracked by using optical flow and the variations are retargeted to the 3D face model. At the same time, we exploit the RBF (Radial Basis Function) to deform the local area of the face model around the major feature points. Consequently, facial expression synthesis is done by directly tracking the variations of the major feature points and indirectly estimating the variations of the regional feature points. From the experiments, we can prove that the proposed vision-based facial expression cloning method automatically estimates the 3D head pose and produces realistic 3D facial expressions in real time.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.1
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• pp.106-123
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• 2024

This article takes the talk show "Beast Town" as an example to introduce the overall technical solution, technical difficulties and countermeasures for the combination of cartoon virtual characters and virtual studio technology, providing reference and experience for the multi-scenario application of digital humans. Compared with the live broadcast that combines reality and reality, we have further upgraded our virtual production technology and digital human-driven technology, adopted industry-leading real-time virtual production technology and monocular camera driving technology, and launched a virtual cartoon character talk show - "Beast Town" to achieve real Perfectly combined with virtuality, it further enhances program immersion and audio-visual experience, and expands infinite boundaries for virtual manufacturing. In the talk show, motion capture shooting technology is used for final picture synthesis. The virtual scene needs to present dynamic effects, and at the same time realize the driving of the digital human and the movement with the push, pull and pan of the overall picture. This puts forward very high requirements for multi-party data synchronization, real-time driving of digital people, and synthetic picture rendering. We focus on issues such as virtual and real data docking and monocular camera motion capture effects. We combine camera outward tracking, multi-scene picture perspective, multi-machine rendering and other solutions to effectively solve picture linkage and rendering quality problems in a deeply immersive space environment. , presenting users with visual effects of linkage between digital people and live guests.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.2
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• pp.136-144
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• 2014

The existing conventional motion controller does not perform well in the presence of nonlinear properties, uncertain factors, and servo lag phenomena of industrial actuators. Hence, a feasible and effective fuzzy self-tuning proportional integral derivative (PID) and feed-forward control scheme is introduced to overcome these problems. In this design, a fuzzy tuner is used to tune the PID parameters resulting in the rejection of the disturbance, which achieves better performance. Then, both velocity and acceleration feed-forward units are added to considerably reduce the tracking error due to servo lag. To verify the capability and effectiveness of the proposed control scheme, the hardware configuration includes digital signal processing (DSP) which plays the main role, dual-port RAM (DPRAM) to guarantee rapid and reliable communication with the host, field-programmable gate array (FPGA) to handle the task of the address decoder and receive the feed-back encoder signal, and several peripheral logic circuits. The results from the experiments show that the proposed motion controller has a smooth profile, with high tracking precision and real-time performance, which are applicable in various manufacturing fields.