H. Li, P. Roivainen, R. Forchheimer, 3-D motion estimation in model-based facial image coding, IEEE Transations on Pattern Analysis and Machine Intelligence 15 (6) (1993) 545--555.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....both the computer vision and signal processing communities. This interest is motivated by the broad range of potential applications for systems able to code and interpret the information they contain. Examples include personal identification and access control [3,19] low bandwidth communication [11,13,18], mugshot recognition [8] and human computer interaction [1] The functionality required to tackle these applications successfully can be expressed in terms of a number of generic capabilities: feature location and tracking, person identification, expression recognition, pose recovery, and ....

....a face image using 50 expansion coefficients and subsequently reconstruct an approximation using these parameters. Model based coding and reconstruction has re ceived a considerable attention in the literature. Models based on the physical and anatomical structure of faces [18] and 3D models [11] have been used to account for the variability in appearance due to changes in pose and expression. Face image interpretation techniques can be divided into two main categories: those employing geometrical features and those using grey level informa tion. Techniques based on geometrical ....

Haibo Li, P. Roivainen and R. Forchheimer. 3-D Motion Estimation in Model-Based Facial Image Coding. IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol 15, no 6, pp 545-555, 1993.

.... [16, 23, 21, 9] measurements of the shapes of facial features and their spatial arrangements [13] holistic spatial pattern analysis using techniques based on principal components analysis (PCA) 2, 19, 13] and methods for relating face images to physical models of the facial skin and musculature [16, 22, 14, 9]. Most of the previous work employed datasets of posed expressions collected under controlled image conditions. Subjects deliberately faced the camera and the facial expressions were temporally segmented. Extending these systems to spontaneous facial behavior is a critical step forward for ....

H. Li, P. Roivainen, and R. Forchheimer. 3-d motion estimation in model-based facial image coding. IEEE Transactions on Pattern Analysis and Machine Intelligence, 15(6):545--555, 1993.

....a moving object from an image sequence is useful in applications such as photogrammetry, passivenavigation, industry inspection and human computer interfaces, etc. In this paper, we are interested in the model based pose estimation algorithm. A number of work have been done by previous researchers [13,7,4, 3]. Some of them are optical flow based[4] which require massive computation power and are not suitable for real time applications. Others use nonlinear iterativemethodssuch as Newton s method, which is sensitive to the initial guess supplied. Our interest is in developing an efficient algorithm ....

....in applications such as photogrammetry, passivenavigation, industry inspection and human computer interfaces, etc. In this paper, we are interested in the model based pose estimation algorithm. A number of work have been done by previous researchers [13,7,4, 3] Some of them are optical flow based[4], which require massive computation power and are not suitable for real time applications. Others use nonlinear iterativemethodssuch as Newton s method, which is sensitive to the initial guess supplied. Our interest is in developing an efficient algorithm which is suitable for real time ....

H.Li, P.Roivainen, and R.Forchheimer. 3-d motion estimation in model-based facial image coding. IEEE Trans. Pattern Anal. Machine Intell., 15(6):545--555, June 1993.

....face, and a prepared representative model of the individual. This paper focuses on stages highlighted in orange. II. BACKGROUND PDFA requires facial sensing, and computer vision research is extensive in this area [6, 7, 8, 10, 13, 30 32] One approach uses whole image optical flow measures [3, 4, 33]. These are currently too slow for use in a live performance. When live performance is important, as in virtual tele conferencing, tracked feature points can provide sparse but real time updates. We employ an existing commercial feature tracking system [11] that works without markers. It reports ....

H. Li, P. Roivainen, R.Forchheimer, 3-D Motion Estimation in Model-Based Facial Image Coding, IEEE PAMI, 1993, 15(6), pp. 545-555

....detailed facial shapes such as the wrinkles on a face are extracted by Lighting Switch Photometry. Azarbayejani et al. 5] use an extended Kalman filter to recover the rigid motion parameters of a head. Saulnier et al. 113] report a template based method for tracking and animation. Li et al. [64] use the Candid model for 3D motion estimation for model based image coding. Masse et al. 73] use optical flow and principal direction analysis for automatic lip reading. 12. Mouth Animation Among the regions of the face, the mouth is the most complicated in terms of its anatomical structure ....

H. Li, P. Roivainen, R. Forchheimer, 3-D Motion Estimation in Model Based Facial Image Coding, IEEE Transaction on Pattern Analysis and Machine Intelligence, June 1993, vol. 15, No 6, pp. 545555

....face, and a prepared representative model of the individual. This paper focuses on stages highlighted in orange. II. BACKGROUND PDFA requires facial sensing, and computer vision research is extensive in this area [6, 7, 8, 10, 13, 30 32] One approach uses whole image optical flow measures [3, 4, 33]. These are currently too slow for use in a live performance. When live performance is important, as in virtual tele conferencing, tracked feature points can provide sparse but real time updates. We employ an existing commercial feature tracking system [11] that works without markers. It reports ....

H. Li, P. Roivainen, R.Forchheimer, 3-D Motion Estimation in Model-Based Facial Image Coding, IEEE PAMI, 1993, 15(6), pp. 545-555

....faces can conversational interfaces [5] interactive kiosks [24] and robots [11] start to understand more features of natural face to face dialogue. And only by gathering accurate motion estimates of faces can facial animation systems be automated [27] or videos of faces be compressed effectively [15, 16, 27]. Even though some of these systems do not need to know about the user s appearance, having an accurate estimate of the face shape is still important, # D. DeCarlo is with the Department of Computer Science and Center for Cognitive Science, Rutgers University, New Brunswick, NJ. E mail: ....

....a certain degree of accuracy. It works quite well for models of human faces, for instance, where shape parameters describe an individual s appearance, while motion parameters encode the location of the head, as well as facial displays and expressions. This division is often built into face models [3, 6, 16, 19, 28] to simplify model construction or estimation, and has been used to facilitate learning the variability of motions for a class of objects [25] The ultimate goal of this separation is to produce an estimation problem with lower dimension. During estimation, the change in the shape parameters ....

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H. Li, P. Roivainen, and R. Forchheimer. 3-D motion estimation in model-based facial image coding. IEEE Pattern Analysis and Machine Intelligence, 15(6):545--555, June 1993.

....the rotation of the object in 3D space often leads to a nonlinear formulation which increases dramatically the computational requirement for the solution. In this paper, we are interested in the model based pose estimation algorithm. Anumber of work have been done by previous researchers [36,31,19,13,8]. Some of them are optical flow based[13] which require massive computation power. Others use nonlinear iterative methods suchas Newton s method, which is sensitive to the initial guess supplied. Our interest is in developing an efficient algorithm which is suitable for various applications on ....

....leads to a nonlinear formulation which increases dramatically the computational requirement for the solution. In this paper, we are interested in the model based pose estimation algorithm. Anumber of work have been done by previous researchers [36,31,19,13,8] Some of them are optical flow based[13], which require massive computation power. Others use nonlinear iterative methods suchas Newton s method, which is sensitive to the initial guess supplied. Our interest is in developing an efficient algorithm which is suitable for various applications on human motion analysis. This area is ....

H.Li, P.Roivainen, and R.Forchheimer. 3-d motion estimation in model-based facial image coding. IEEE Trans. Pattern Anal. Machine Intell., 15(6):545--555, June 1993.

....are approximated by simply rendering the 3 D head model. In our model based coder all FAPs are estimated simultaneously using a hierarchical optical ow based method starting with an image of 88 x 72 pixels and ending with CIF resolution. In the optimization an analysis synthesis loop is employed [8]. The mean squared error between the rendered head model and the current video frame is minimized by estimating changes of the FAPs. To simplify the optimization in the high dimensional parameter space, a linearized solution is directly computed using information from the optical ow and motion ....

H. Li, P. Roivainen, and R. Forchheimer, \3-D motion estimation in model-based facial image coding", IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 15, no. 6, pp. 545-555, Jun. 1993.

....Video production, realistic computer graphics, multimedia interfaces and medical visualisation are some of the applications that may benefit by exploiting the potential of model based schemes. Current model based image coding schemes may be divided into two broad categories. The first category [2,8,12,13,27] is knowledgebased and uses explicit human head models for 0923 5965 98 see front matter # 1998 Elsevier Science B.V. All rights reserved. PII: S 0 9 2 3 5 9 6 5 ( 9 8 ) 0 0 0 3 0 7 coding primarily videoconferencing schemes. A second analysis by synthesis group of methods [4,14,18] is ....

L. Haibo, P. Roivanen, R. Forcheimer, 3D motion estimation in model-based facial image coding, TPAMI 15 (June 1993) 545---555.

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H. Li, P. Roivainen, and R. Forchheimer. 3-d motion estimation in model-based facial image coding. IEEE Trans. on Pattern Analysis and Machine Intelligence, pages 545--555, 1993.

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H. Li and et al. 3-d motion estimation in model-based facial image coding. IEEE Trans. on PAMI, pages 545--555, 1993.

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H. Li, P. Roivainen, R. Forchheimer, 3-D motion estimation in model-based facial image coding, IEEE Transations on Pattern Analysis and Machine Intelligence 15 (6) (1993) 545--555.

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H. Li, P. Roivainen, and R. Forcheimer. 3-D motion estimation in model-based facial image coding. IEEE Transactions on Pattern Analysis and Machine Intelligence, 15#6#:545#555, June 1993.

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H. Li, P. Roivainen, and R. Forchheimer. 3-D motion estimation in model-based facial image coding. IEEE Trans. PAMI, 15(6):545--555, June 1993.

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H. Li, P. Roivainen, and R. Forchheimer. 3-D motion estimation in model-based facial image coding. IEEE Trans. PAMI, 15(6):545--555, June 1993.

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H. Li, P. Roivainen, and R. Forcheimer. 3-D motion estimation in model-based facial image coding. IEEE Transactions on Pattern Analysis and Machine Intelligence, 15(6):545--555, June 1993.

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H. Li, P. Roivainen, and R. Forchheimer. 3-D motion estimation in model-based facial image coding. In IEEE Transactions on Pattern Analysis and Machine Intelligence, pages 545--555, 1993.

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H. Li, P. Roivainen, and R. Forchheimer. 3-D motion estimation in model-based facial image coding. IEEE Trans. PAMI, 15(6):545--555, June 1993.

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H. Li, P. Roivainen, and R. Forchheimer. 3-D motion estimation in model-based facial image coding. IEEE Transactions on Pattern Analysis and Machine Intelligence, 15(6):545--555, Jun. 1993.

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Li H, Rovainen P, Forcheimer R (1993) 3-D motion estimation in model-based facial image coding. IEEE Trans Pattern Anal Mach Intell 15(6):545--555

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H. Li, P. Roivainen, and R. Forchheimer. 3-D motion estimation in model-based facial image coding. IEEE Pattern Analysis and Machine Intelligence, 15(6):545--555, June 1993.

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Li Haibo, Roivainen P, Forchheimer R '3-D Motion Estimation in Model Based Facial Image Coding' IEEE Transaction on Pattern Analysis and Machine Intelligence, June 1993, Vol. 15, No 6, 545-555.

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H. Li, P. Roivainen, and R. Forchheimer. 3D motion estimation in model-based facial image coding. IEEE Transactions on Pattern Analysis and Machine Intelligence, 15(6):545--555, June 1993.

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H. Li, P. Roivainen, and R. Forchheimer. 3D motion estimation in model-based facial image coding. IEEE Transactions on Pattern Analysis and Machine Intelligence, 15(6):545--555, June 1993.

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