• The KIPS Transactions:PartB
• /
• v.14B no.4
• /
• pp.311-320
• /
• 2007

This paper presents vision-based 3D facial expression animation technique and system which provide the robust 3D head pose estimation and real-time facial expression control. Many researches of 3D face animation have been done for the facial expression control itself rather than focusing on 3D head motion tracking. However, the head motion tracking is one of critical issues to be solved for developing realistic facial animation. In this research, we developed an integrated animation system that includes 3D head motion tracking and facial expression control at the same time. The proposed system consists of three major phases: face detection, 3D head motion tracking, and facial expression control. For face detection, with the non-parametric HT skin color model and template matching, we can detect the facial region efficiently from video frame. For 3D head motion tracking, we exploit the cylindrical head model that is projected to the initial head motion template. Given an initial reference template of the face image and the corresponding head motion, the cylindrical head model is created and the foil head motion is traced based on the optical flow method. For the facial expression cloning we utilize the feature-based method, The major facial feature points are detected by the geometry of information of the face with template matching and traced by optical flow. Since the locations of varying feature points are composed of head motion and facial expression information, the animation parameters which describe the variation of the facial features are acquired from geometrically transformed frontal head pose image. Finally, the facial expression cloning is done by two fitting process. The control points of the 3D model are varied applying the animation parameters to the face model, and the non-feature points around the control points are changed by use of Radial Basis Function(RBF). From the experiment, we can prove that the developed vision-based animation system can create realistic facial animation with robust head pose estimation and facial variation from input video image.

• Journal of Broadcast Engineering
• /
• v.17 no.5
• /
• pp.838-850
• /
• 2012

In this paper, we propose a novel algorithm that generates multi-view images by using various image features obtained from the given stereoscopic images. In the proposed algorithm, we first create an intensity gradient saliency map from the given stereo images. And then we calculate a block-based optical flow that represents the relative movement(disparity) of each block with certain size between left and right images. And we also obtain the disparities of feature points that are extracted by SIFT(scale-invariant We then create a disparity saliency map by combining these extracted disparity features. Disparity saliency map is refined through the occlusion detection and removal of false disparities. Thirdly, we extract straight line segments in order to minimize the distortion of straight lines during the image warping. Finally, we generate multi-view images by grid mesh-based image warping algorithm. Extracted image features are used as constraints during grid mesh-based image warping. The experimental results show that the proposed algorithm performs better than the conventional DIBR algorithm in terms of visual quality.

• Journal of KIISE:Computer Systems and Theory
• /
• v.33 no.8
• /
• pp.536-546
• /
• 2006

Painterly animation is a method that expresses painterly images with a hand-painted appearance from a video, and the most crucial element for it is the temporal coherence of brush strokes between frames. A motion map is proposed in this paper as a solution to the issue of maintaining the temporal coherence in the brush strokes between the frames. A motion map is the region that frame-to-frame motions have occurred. Namely, this map refers to the region frame-to-frame edges move by the motion information with the motion occurred edges as a starting point. In this paper, we employ the optical flow method and block-based method to estimate the motion information. The method that yielded the biggest PSNR using the motion information (the directions and magnitudes) acquired by various methods of motion estimation has been chosen as the final motion information to form a motion map. The created motion map determine the part of the frame that should be re-painted. In order to express painterly images with a hand- painted appearance and maintain the temporal coherence of brush strokes, the motion information was applied to only the strong edges that determine the directions of the brush strokes. Also, this paper seek to reduce the flickering phenomenon between the frames by using the multiple exposure method and the difference map created by the difference between images of the source and the canvas. Maintenance of the coherence in the direction of the brush strokes was also attempted by a local gradient interpolation to maintain the structural coherence.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.36 no.7C
• /
• pp.421-427
• /
• 2011

The importance of the real-time object recognition and tracking field has been growing steadily due to rapid advancement in the computer vision applications industry. As is well known, the mean-shift algorithm is widely used in robust real-time object tracking systems. Since the mentioned algorithm is easy to implement and efficient in object tracking computation, many say it is suitable to be applied to real-time object tracking systems. However, one of the major drawbacks of this algorithm is that it always converges to a local mode, failing to perform well in a cluttered environment. In this paper, an Optical Flow-based algorithm which fits for real-time recognition of multiple moving objects is proposed. Also in the tests, the newly proposed method contributed to raising the similarity of multiple moving objects, the similarity was as high as 0.96, up 13.4% over that of the mean-shift algorithm. Meanwhile, the level of pixel errors from using the new method keenly decreased by more than 50% over that from applying the mean-shift algorithm. If the data processing speed in the video surveillance systems can be reduced further, owing to improved algorithms for faster moving object recognition and tracking functions, we will be able to expect much more efficient intelligent systems in this industrial arena.

• Journal of Practical Engineering Education
• /
• v.16 no.3_spc
• /
• pp.391-399
• /
• 2024

All highway toll gates in Korea use low-speed WIM(Weight-In-Motion) to block overloaded cargo vehicles from entering the main highway, but some cargo vehicle owners are illegally modifying vehicles to operate variable axles and evading crackdowns by manipulating the axles. In previous studies detect all tires of a running vehicle were detected to determine whether there is axle manipulation. However, because the vehicle entry area at the highway toll gate checkpoint is very narrow, there is a problem that it is realistically difficult to film all tires of the entering vehicle in one video frame. In this paper, we proposed a system that can determine whether the axle is being operated through changes in the height of the vehicle's cargo box rather than by detecting tires. To detect changes in the height of a cargo box, we propose a method to extract the representative line of the cargo box using Hough transform and then measure the change in height of the representative line to detect the change in height of the cargo box. In addition, we propose a method to detect changes in the vertical height of a cargo box by accumulating motion vectors of pixels within a certain area of the image using optical flow. And the two methods were compared and their advantages and disadvantages were analyzed and presented.