• Proceedings of the IEEK Conference
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• 2001.06d
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• pp.219-222
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• 2001

Moving objects in video data are main elements for video analysis and retrieval. In this paper, we propose a new algorithm for tracking and segmenting moving objects in color image sequences that include complex camera motion such as zoom, pan and rotating. The Proposed algorithm is based on the Mean-shift color segmentation and stochastic region matching method. For segmenting moving objects, each sequence is divided into a set of similar color regions using Mean-shift color segmentation algorithm. Each segmented region is matched to the corresponding region in the subsequent frame. The motion vector of each matched region is then estimated and these motion vectors are summed to estimate global motion. Once motion vectors are estimated for all frame of video sequences, independently moving regions can be segmented by comparing their trajectories with that of global motion. Finally, segmented regions are merged into the independently moving object by comparing the similarities of trajectories, positions and emerging period. The experimental results show that the proposed algorithm is capable of segmenting independently moving objects in the video sequences including complex camera motion.

• 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.

• The Journal of Korea Robotics Society
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• v.14 no.2
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• pp.104-113
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• 2019

Object manipulation in cluttered environments remains an open hard problem. In cluttered environments, grasping objects often fails for various reasons. This paper proposes a novel task and motion planning scheme to grasp objects obstructed by other objects in cluttered environments. Task and motion planning (TAMP) aims to generate a sequence of task-level actions where its feasibility is verified in the motion space. The proposed scheme contains an open-loop consisting of three distinct phases: 1) Generation of a task-level skeleton plan with pose references, 2) Instantiation of pose references by motion-level search, and 3) Re-planning task based on the updated state description. By conducting experiments with simulated robots, we show the high efficiency of our scheme.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.5B
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• pp.913-924
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• 2000

This paper proposes an efficient descriptor for objects motion trajectory and a video retrieval algorithm based on objects motion trajectory. The algorithm describes parameters with coefficients of 2-order polynomial for objects motion trajectory after segmentation of the object from the scene. The algorithm also identifies types, intervals, and magnitude of global motion caused by camera motion and indexes them with 6-affine parameters. This paper implements content-based video retrieval using similarity-match between indexed parameters and queried ones for objects motion trajectory. The proposed algorithm will support not only faster retrieval for general videos but efficient operation for unmanned video surveillance system.

• The Journal of the Korea Contents Association
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• v.7 no.4
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• pp.170-177
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• 2007

When buoyant objects appear in contents, it is helpful in developing contents to express their attributes such as their length, width, weight, and velocity, and the magnitude and direction of regular waves dynamically. Therefore, we verify how the attributes of buoyant objects and the characteristics of waves cause the heaving motion of buoyant objects to change by using the equation of motion used in the naval architecture and ocean engineering. Our research results may help contents developers to develop contents with buoyant objects even if they do not understand the naval architecture and ocean engineering well. We show that we can calculate the motion of buoyant objects dynamically even if the velocity of buoyant objects or the characteristics of waves change dynamically. In the future, we will study how buoyant objects move on the irregular waves, and develop engines for buoyant objects on the real sea.

• Journal of KIISE:Computer Systems and Theory
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• v.37 no.4
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• pp.239-245
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• 2010

Previous painterly rendering techniques normally use image gradients for stroke generation. Although image gradients are useful for expressing object shapes, it is difficult to express the flow or movements of objects of objects. In real painting, the use of brush strokes corresponding to the actual movement of objects allows viewers to recognize objects’ motion better and express the liveliness of the objects much more. In this paper, we propose a novel painterly stroke generation algorithm to express dynamic objects based on their motion information. We first extract motion information (magnitude, direction) of a scene from a set of image sequences from the same view. Then the motion directions are used for determining stroke orientations in the regions with significant motions. Where little motion is observed, image gradients are used for determining stroke orientations. Our algorithm is useful for realistically and dynamically representing moving objects.

• Journal of Mechanical Science and Technology
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• v.15 no.3
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• pp.300-308
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• 2001

Tracking of moving objects within video streams is a complex and time-consuming process. Large number of moving objects increases the time for computation of tracking the moving objects. Because of large computations, there are real-time processing problems in tracking of moving objects. Also, the change of environment causes errors in estimation of tracking information. In this paper, we present a new method for tracking of moving objects using optical flow motion analysis. Optical flow represents an important family of visual information processing techniques in computer vision. Segmenting an optical flow field into coherent motion groups and estimating each underlying motion are very challenging tasks when the optical flow field is projected from a scene of several moving objects independently. The problem is further complicated if the optical flow data are noisy and partially incorrect. Optical flow estimation based on regulation method is an iterative method, which is very sensitive to the noisy data. So we used the Combinatorial Hough Transform (CHT) and Voting Accumulation for finding the optimal constraint lines. To decrease the operation time, we used logical operations. Optical flow vectors of moving objects are extracted, and the moving information of objects is computed from the extracted optical flow vectors. The simulation results on the noisy test images show that the proposed method finds better flow vectors and more correctly estimates the moving information of objects in the real time video streams.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.1
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• pp.62-69
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• 2008

A specialized anthropomorphic robot hand which can be attached to the biped humanoid robot MAHRU-R in KIST, has been developed. This built-in type hand consists of three fingers and a thumb with total four DOF(Degrees of Freedom) where the finger mechanism is well designed for grasping typical objects stably in human's daily activities such as sphere and cylinder shaped objects. The restriction of possible motions and the limitation of grasping objects arising from the reduction of DOF can be overcome by reflecting a typical human finger's motion profile to the design procedure. As a result, the developed hand can imitate not only human hand's shape but also its motion in a compact and efficient manner. Also this novel robot hand can perform various human hand gestures naturally and grasp normal objects with both power and precision grasping capability.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.8
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• pp.41-53
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• 1993

The tasks which detect and track moving objects, by analyzing dynamic images taken at a constant time interval, are essential in various applications. This paper suggests how to utilize domain-specific knowledge and motional knowledge for detecting and tracking moving objects. That is, The trajectory information of a moving object is to be used for generating hypotheses on expected motion and expected position of moving objects, and the domain-specific knowledge is to be used for verifying the generated hypotheses.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.955-958
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• 1998

This paper describes the algorithm which extracts moving vehicles from sequential images and tracks those vehicles using Kalman filter. This work is composed of a motion segmentation stage which extracts moving objects from sequential images and gets features of objects, and a motion estimation stage which estimates the position and the motion of moving objects using Kalman filter. In the motion estimation stage, applying to affine motion model we divided the Kalman filter into position filter and velocity filter to employ linear Kalman filter. Multi-target tracking requires a data association component that decides which measurement to use for updating the state of which object. We use pattern recognition method to solve this problem.