• Title/Summary/Keyword: Lucas-Kanade

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Digital Image Stabilization Based on Edge Detection and Lucas-Kanade Optical Flow (Edge Detection과 Lucas-Kanade Optical Flow 방식에 기반한 디지털 영상 안정화 기법)

  • Lee, Hye-Jung;Choi, Yun-Won;Kang, Tae-Hun;Lee, Suk-Gyu
    • The Journal of Korea Robotics Society
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    • v.5 no.2
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    • pp.85-92
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    • 2010
  • In this paper, we propose a digital image stabilization technique using edge detection and Lucas-Kanade optical flow in order to minimize the motion of the shaken image. The accuracy of motion estimation based on block matching technique depends on the size of search window, which results in long calculation time. Therefore it is not applicable to real-time system. In addition, since the size of vector depends on that of block, it is difficult to estimate the motion which is bigger than the block size. The proposed method extracts the trust region using edge detection, to estimate the motion of some critical points in trust region based on Lucas-Kanade optical flow algorithm. The experimental results show that the proposed method stabilizes the shaking of motion image effectively in real time.

Face detection using haar-like feature and Tracking with Lucas-Kanade feature tracker (Haar-like feature를 이용한 얼굴 검출과 추적을 위한 Lucas-Kanade특징 추적)

  • Kim, Ki-Sang;Kim, Se-Hoon;Park, Gene-Yong;Choi, Hyung-Il
    • 한국HCI학회:학술대회논문집
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    • 2008.02a
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    • pp.835-838
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    • 2008
  • In this paper, we present automatic face detection and tracking which is robustness in rotation and translation. Detecting a face image, we used Haar-like feature, which is fast detect facial image. Also tracking, we applied Lucas-Kanade feature tracker and KLT algorithm, which has robustness for rotated facial image. In experiment result, we confirmed that face detection and tracking which is robustness in rotation and translation.

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Algorithm for Arbitrary Point Tracking using Pyramidal Optical Flow (피라미드 기반 광류 추정을 이용한 영상 내의 임의의 점 추적 알고리즘)

  • Lee, Jae-Kwang;Park, Chang-Joon
    • Journal of Korea Multimedia Society
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    • v.10 no.11
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    • pp.1407-1416
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    • 2007
  • This paper describes an algorithm for arbitrary point tracking using pyramidal optical flow. The optical flow is calculated based on the Lucas-Kanade's optical flow estimation in this paper. The image pyramid is employed to calculate a big motion while being sensitive to a small motion. Furthermore, a rectification process is proposed to reduce the error which is increased as it goes down to the lower level of the image pyramid. The accuracy of the optical flow estimation was increased by using some constraints and sub-pixel interpolation of the optical flow and this makes our algorithm to track points in which they do not have features such as edges or corners. The proposed algorithm is implemented and primary results are shown in this paper.

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Handled in real-time tracking of moving object occlusion (가림현상에 대처한 실시간 이동 물체 추적)

  • Kim, Hag-Hee;Yun, Han-Kyung
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.4 no.3
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    • pp.158-166
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    • 2011
  • Generally, moving object tracking used Lucas-Kanade feature tracking method which is strong in movement, rotation and size. But this method is very weak of occlusion by background or another object and so on. In this case, this method tracks backgrounds or another objects instead a moving object, or a tracking is finished. In order to solve this problem, we proposes Lucas-Kanade feature tracking method which introduce a destimation function and prediction function.

Automatic Face Region Detection and Tracking for Robustness in Rotation using the Estimation Function (평가 함수를 사용하여 회전에 강건한 자동 얼굴 영역 검출과 추적)

  • Kim, Ki-Sang;Kim, Gye-Young;Choi, Hyung-Il
    • The Journal of the Korea Contents Association
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    • v.8 no.9
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    • pp.1-9
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    • 2008
  • In this paper, we proposed automatic face detection and tracking which is robustness in rotation. To detect a face image in complicated background and various illuminating conditions, we used face skin color detection. we used Harris corner detector for extract facial feature points. After that, we need to track these feature points. In traditional method, Lucas-Kanade feature tracker doesn't delete useless feature points by occlusion in current scene (face rotation or out of camera). So we proposed the estimation function, which delete useless feature points. The method of delete useless feature points is estimation value at each pyramidal level. When the face was occlusion, we deleted these feature points. This can be robustness to face rotation and out of camera. In experimental results, we assess that using estimation function is better than traditional feature tracker.

On the Spatial Registration Considering Image Exposure Compensation (영상의 노출 보정을 고려한 공간 정합 알고리듬 연구)

  • Kim, Dong-Sik;Lee, Ki-Ryung
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.44 no.2 s.314
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    • pp.93-101
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    • 2007
  • To jointly optimize the spatial registration and the exposure compensation, an iterative registration algorithm, the Lucas-Kanade algorithm, is combined with an exposure compensation algorithm, which is based on the histogram transformation function. Based on a simple regression model, a nonparametric estimator, the empirical conditional mean, and its polynomial fitting are used as histogram transformation functions for the exposure compensation. Since the proposed algorithm is composed of separable optimization phases, the proposed algorithm is more advantageous than the joint approaches of Mann and Candocia in the aspect of implementation flexibility. The proposed algorithm performs a better registration for real images than the case of registration that does not consider the exposure difference.

Recognition System of Slope Condition Using Image and Laser Measuring Instrument (영상 및 레이저 계측기를 통한 경사면 상황인식 시스템)

  • Han, Sang-Hun;Han, Youngjoon
    • IEMEK Journal of Embedded Systems and Applications
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    • v.9 no.4
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    • pp.219-227
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    • 2014
  • Natural disasters such as a ground collapse and a landslide have broken out due to the climate change of the Korea and the reckless expansion of cities and roads. The climate changes and the reckless urbanization have made the ground weak. Thus, it is important to keep a close eye on the highly weakened landslide and to prevent its natural disasters. In order to prevent these disasters, this paper presents a system of recognizing the road slide condition by measuring the displacements using laser scanner instrument. The previous system of monitoring the road slide has some problems as inaccurate recognition due to using only images from a camera, or expensive system such as artificial satellites and aircraft systems. To solve this problem, our proposed system uses the 3D range data from the laser scanner for measuring the accurate displacement of the road slide and optical flows from the Lucas-Kanade algorithm for recognizing the road slide in the image.

The Study of Pre-processing Algorithm for Improving Efficiency of Optical Flow Method on Ultrasound Image (초음파 영상에서의 Optical Flow 추적 성능 향상을 위한 전처리 알고리즘 개발 연구)

  • Kim, Sung-Min;Lee, Ju-Hwan;Roh, Seung-Gyu;Park, Sung-Yun
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.47 no.5
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    • pp.24-32
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    • 2010
  • In this study, we have proposed a pre-processing algorithm newly developed for improving the tracking efficiency of the optical flow method. The developed pre-processing algorithm consists of a median filter, binarization, morphology, canny edge, contour detecting and an approximation method. In order to evaluate whether the optical flow tracking capacity increases, this study applied the pre-processing algorithm to the Lucas-Kanade(LK) optical flow algorithm, and comparatively analyzed its images and tracking results with those of optical flow without the pre-processing algorithm and with the existing pre-processing algorithm(composed of median filter and histogram equalization). As a result, it was observed that the tracking performance derived from the LK optical flow algorithm with the pre-processing algorithm, shows better tracking accuracy, compared to the one without the pre-processing algorithm and the one with the existing pre-processing algorithm. It seems to have resulted by successful segmentation for characteristic areas and subdivision into inner and outer contour lines.

Optimal Facial Emotion Feature Analysis Method based on ASM-LK Optical Flow (ASM-LK Optical Flow 기반 최적 얼굴정서 특징분석 기법)

  • Ko, Kwang-Eun;Park, Seung-Min;Park, Jun-Heong;Sim, Kwee-Bo
    • Journal of the Korean Institute of Intelligent Systems
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    • v.21 no.4
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    • pp.512-517
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    • 2011
  • In this paper, we propose an Active Shape Model (ASM) and Lucas-Kanade (LK) optical flow-based feature extraction and analysis method for analyzing the emotional features from facial images. Considering the facial emotion feature regions are described by Facial Action Coding System, we construct the feature-related shape models based on the combination of landmarks and extract the LK optical flow vectors at each landmarks based on the centre pixels of motion vector window. The facial emotion features are modelled by the combination of the optical flow vectors and the emotional states of facial image can be estimated by the probabilistic estimation technique, such as Bayesian classifier. Also, we extract the optimal emotional features that are considered the high correlation between feature points and emotional states by using common spatial pattern (CSP) analysis in order to improvise the operational efficiency and accuracy of emotional feature extraction process.