• Journal of Sensor Science and Technology
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• v.21 no.2
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• pp.96-102
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• 2012

This paper addresses photometric distortion problems of a compact 3D scanning sensor which is composed of a micro-size and inexpensive camera-projector system. Recently, many micro-size cameras and projectors are available. However, erroneous 3D scanning results may arise due to the poor and nonlinear photometric properties of the sensors. This paper solves two inherent photometric distortions of the sensors. First, the response functions of both the camera and projector are derived from the least squares solutions of passive and active calibration, respectively. Second, vignetting correction of the vision camera is done by using a conventional method, however the projector vignetting is corrected by using the planar homography between the image planes of the projector and camera, respectively. Experimental results show that the proposed technique enhances the linear properties of the phase patterns that are generated by the sensor.

• International Journal of Control, Automation, and Systems
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• v.1 no.4
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• pp.495-502
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• 2003

This paper focuses on the implementation of an efficient tracking method of a moving object using optimal representative blocks by way of a pan-tilt camera. The key idea is derived from the fact that when the image size of a moving object is shrunk in an image frame according to the distance between the mobile robot camera and the object in motion, the tracking performance of a moving object can be improved by reducing the size of representative blocks according to the object image size. Motion estimations using Edge Detection (ED) and Block-Matching Algorithm (BMA) are regularly employed to track objects by vision sensors. However, these methods often neglect the real-time vision data since these schemes suffer from heavy computational load. In this paper, a representative block able to significantly reduce the amount of data to be computed, is defined and optimized by changing the size of representative blocks according to the size of the object in the image frame in order to improve tracking performance. The proposed algorithm is verified experimentally by using a two degree-of- freedom active camera mounted on a mobile robot.

• The Journal of Korea Robotics Society
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• v.13 no.1
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• pp.31-37
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• 2018

Recently, the safety in vehicle also has become a hot topic as self-driving car is developed. In passive safety systems such as airbags and seat belts, the system is being changed into an active system that actively grasps the status and behavior of the passengers including the driver to mitigate the risk. Furthermore, it is expected that it will be possible to provide customized services such as seat deformation, air conditioning operation and D.W.D (Distraction While Driving) warning suitable for the passenger by using occupant information. In this paper, we propose robust vehicle occupant detection algorithm based on RGB-Depth-Thermal camera for obtaining the passengers information. The RGB-Depth-Thermal camera sensor system was configured to be robust against various environment. Also, one of the deep learning algorithms, OpenPose, was used for occupant detection. This algorithm is advantageous not only for RGB image but also for thermal image even using existing learned model. The algorithm will be supplemented to acquire high level information such as passenger attitude detection and face recognition mentioned in the introduction and provide customized active convenience service.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.3
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• pp.694-701
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• 2004

In this paper, we proposed a feature-based tracking system that traces moving objects with a pan-tilt camera after separating the global motion of an active camera and the local motion of moving objects. The tracking system traces only the local motion of the comer features in the foreground objects by finding the block motions between two consecutive frames using a block-based motion estimation and eliminating the global motion from the block motions. For the robust estimation of the camera motion using only the background motion, we suggest a dominant motion extraction to classify the background motions from the block motions. We also propose an efficient clustering algorithm based on the attributes of motion trajectories of corner features to remove the motions of noise objects from the separated local motion. The proposed tracking system has demonstrated good performance for several test video sequences.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.11
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• pp.2839-2852
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• 2013

Context-awareness is an essential part of ubiquitous computing, and over the past decade video based activity recognition (VAR) has emerged as an important component to identify user's context for automatic service delivery in context-aware applications. The accuracy of VAR significantly depends on the performance of the employed human body segmentation algorithm. Previous human body segmentation algorithms often engage modeling of the human body that normally requires bulky amount of training data and cannot competently handle changes over time. Recently, active contours have emerged as a successful segmentation technique in still images. In this paper, an active contour model with the integration of Chan Vese (CV) energy and Bhattacharya distance functions are adapted for automatic human body segmentation using depth cameras for VAR. The proposed technique not only outperforms existing segmentation methods in normal scenarios but it is also more robust to noise. Moreover, it is unsupervised, i.e., no prior human body model is needed. The performance of the proposed segmentation technique is compared against conventional CV Active Contour (AC) model using a depth-camera and obtained much better performance over it.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.5
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• pp.472-478
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• 2015

This paper describes the design of the active optical compensation movements(at focal plane, secondary mirror) for the image stabilization of a small satellite camera. The movements can correct optical misalignment on-line and directly compensate vibration disturbances in the focal plane. Since the devices are installed inside the space camera, it has an remarkable advantage to deal with the structural deformation of a space camera effectively. In this paper, the requirements of the active optical compensation movements for 1m GSD small satellite camera have been analyzed. Based on the established requirements, the design of the active compensation movements have been conducted. The designed active optical compensation system can control 5 axes movements independently to compensate micro-vibration disturbances in the focal plane and to refocus the optical misaligned satellite camera.

• Proceedings of the IEEK Conference
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• 2003.07d
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• pp.1411-1414
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• 2003

In this paper, vehicle tracking is implemented using parametric active contour. Extract objects from the background area is the essential step in vehicle tracking. We focus our algorithm on the situations such that the camera is fixed. However, if a simple and ordinary algorithm is adapted to achieve real-time processing, it produces much noise and the vehicle tracking results is poor. For this reason, in this paper, we propose a parametric active contour model algorithm to achieve better vehicle tracking. Experimental results show that the performance of the proposed algorithm is satisfactory.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.6
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• pp.27-34
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• 2011

In this paper, we propose an active 3D shape acquisition method based on photometric stereo using camera and flash on a smartphone. Two smartphones are used as the master and slave, in which the slave projects illumination from different locations while the master captures the images and processes photometric stereo algorithm to reconstruct 3D shape. In order to reduce the error, the smartphone's camera is calibrated to overcome the effect of the lens distortion and nonlinear camera sensor response. We apply 5-point algorithm to estimate the pose between smartphone cameras and then estimate lighting direction vector to run the photometric stereo algorithm. Experimental result shows that the proposed system enables us to use smartphone as a 3D camera with low cost and high quality.

• Journal of KIISE:Software and Applications
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• v.34 no.1
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• pp.52-58
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• 2007

In this paper we propose a new robust method to extract accurate human silhouettes indoors with active stereo camera. A prime application is for gesture recognition of mobile robots. The segmentation of distant moving objects includes many problems such as low resolution, shadows, poor stereo matching information and instabilities of the object and background color distributions. There are many object segmentation methods based on color or stereo information but they alone are prone to failure. Here efficient color, stereo and image segmentation methods are fused to infer object and background areas of high confidence. Then the inferred areas are incorporated in graph cut to make human silhouette extraction robust and accurate. Some experimental results are presented with image sequences taken using pan-tilt stereo camera. Our proposed algorithms are evaluated with respect to ground truth data and proved to outperform some methods based on either color/stereo or color/contrast alone.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.2
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• pp.40-49
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• 1992

In this paper,a new approach-using the linear movement of the lens location in a camera and focal distance in each location for the measurement of the depth of the 3-D object from several 2-D images-is proposed. The sharply focused edges are extracted from the images obtained by moving the lens of the camera, that is, the distance between the lens and the image plane, in the range allowed by the camera lens system. Then the depthin formation of the edges are obtained by the lens location. In our method, the accurate and complicated control system of the camera and a special algorithm for tracing the accurate focus point are not necessary, and the method has some advantage that the depth of all objects in a scene are measured by only the linear movement of the lens location of the camera. The accuracy of the extracted depth information is approximately 5% of object distances between 1 and 2m. We can see the possibility of application of the method in the depth measurement of the 3-D objects.