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Feature extraction on the face plays an important role in applications of model based coding and human face recognition. Traditionally, the eyes and mouth are considered to be the most significant features contributing to different facial expressions. However, detecting and tracking the nose shape is non-trivial, and plays an equally important role as eyes and mouth for model based coding, especially for analysis and synthesis of realistic facial expressions. A feature detection method on the facial organ areas is presented. Individual templates are designed for the nostril and nose-side. First, the feature regions are limited to certain areas by using two-stage region growing methods. Second, the pre-defined templates are applied to extract the shape of the nostril and nose-side. Finally, the extracted feature shapes are exploited to guide a facial model to complete an accurate adaptation. The advantage of the proposed scheme is demonstrated by experiments on real video sequences for low bit rate video coding.

Spatially varying sensing (foveation) was first used as a means for image compression in our past research. We extend previous work to address the advantages of foveation in improving the performance of MPEG compression over bandwidth limited channels, such as the Internet. Unlike other approaches to foveating MPEG which used multiresolution representations, we use continuously spatially varying resolution and demonstrate that this approach is indeed advantageous over others. Two parameters, scaling and distortion, are used to allow us to adapt MPEG video to various compression ratios. Experimental results are presented, and can be viewed on the Web, validating our approach.

Conventional stereo imaging uses area CCDs for which depth perception error has been analyzed in our past research (Sahabi and Basu, 1996). In this work we analyze the depth perception error for a stereo system that uses two rotating linear CCD cameras to create cylindrical stereo images. Theoretical analysis shows certain advantages to cylindrical stereo imaging over conventional methods. Initial experimental results are presented to validate the theoretical results. Unlike normal area CCD cameras, rotating linear CCD cameras can capture very high resolution images thereby substantially reducing depth estimation error; more importantly, the error has certain directionally uniform characteristics.

An image-based facial expression synthesis method is presented in this paper for a realistic face animation in model based coding. Differing from the conventional whole texture update method, we propose a partial texture update scheme in active texture areas to reduce the bitrate efficiently. Facial expressions are synthesized using temporal blending and spatial filtering so that a smooth texture fusion can be achieved. Active texture extraction, compression and composition are the principal steps in realizing the proposed scheme. The experiments on video sequences demonstrate the advantage of the proposed algorithm in low cost transmission with high fidelity reproduction. The life-like expressive human faces with wrinkles are generated at a bitrate of less than 40 kb/s.

A complementary catadioptric imaging technique was proposed to solve the problem of low and nonuniform resolution in omnidirectional imaging. To enhance this research, our paper focuses on how to generate a high-resolution panoramic image from the captured omnidirectional image. To avoid the interference between the inner and outer images while fusing the two complementary views, a cross-selection kernel regression method is proposed. First, in view of the complementarity of sampling resolution in the tangential and radial directions between the inner and the outer images, respectively, the horizontal gradients in the expected panoramic image are estimated based on the scattered neighboring pixels mapped from the outer, while the vertical gradients are estimated using the inner image. Then, the size and shape of the regression kernel are adaptively steered based on the local gradients. Furthermore, the neighboring pixels in the next interpolation step of kernel regression are also selected based on the comparison between the horizontal and vertical gradients. In simulation and real-image experiments, the proposed method outperforms existing kernel regression methods and our previous wavelet-based fusion method in terms of both visual quality and objective evaluation.

Due to the limitations of current computer graphics technology mimicing realistic facial textures, such as wrinkles, is very difficult. Facial texture updating and compression are crucial to achieving realistic facial animation for low bit rate model-based coding. In this paper, we present a partial texture updating method for realistic facial expression synthesis with facial wrinkles. First, fiducial points on a face are estimated using a color-based deformable template matching method. Second, an extended dynamic mesh matching algorithm is developed for face tracking. Next, textures of interest (TOI) in the potential expressive wrinkles and mouth?eye texture areas are captured by the detected fiducial points. Among the TOI, the so-called active textures or expressive textures are extracted by exploring temporal correlation information. Finally, the entire facial texture is synthesized using the active texture. Compared to the entire texture updating scheme, partially updating and compressing facial textures significantly reduce the computational complexity and bit rates while still producing an acceptable visual quality. Experiments on the video sequences demonstrate the advantage of the proposed algorithm.

International audience; In this paper, input from an active camera is used for MPEG4 model based coding. First, the background is compensated considering a moving camera (tilt or pan). Second, the talking face is segmented from the compensated background using frame dierences fusion. A morphological ®lter is then applied to make the system less sensitive to noise. Third, Hough Transform and deformable template coupled with color information are exploited to detect the facial features, e.g., eyes, mouth. Fourth, a wireframe model is adapted to the extracted face. The feasibility of the proposed system is demonstrated using a real active video sequence.

In stereo vision the depth of a 3D point is estimated based on the position of its projections on the left and right images. The imaging sensors of cameras, such as charge coupled devices (CCD), consist of discrete pixels. The discretization of images generates uncertainty in estimation of the depth at each 3D point. In this paper, we study the discretization of stereo images that provides the best 3D perception to an end-user. The research will be used to create optimal designs for head-mounted or LCD-based stereo displays.

Using stereo disparity or depth information to detect and track moving objects is receiving increasing attention in recent years. However, this approach suffers from some difficulties, such as synchronisation between two cameras and doubling of the image-data size. Besides, traditional stereo-imaging systems have a limited field of view (FOV), which means that they need to rotate the cameras when an object moves out of view. In this research, the authors present a depth-space partitioning algorithm for performing object tracking using single-camera omni-stereo imaging system. The proposed method uses a catadioptric omni-directional stereo-imaging system to capture omni-stereo image ‘pairs.’ This imaging system has 360° FOV, avoiding the need for rotating cameras when tracking a moving object. In order to estimate omni-stereo disparity, the authors present a depth-space partitioning strategy. It partitions three-dimensional depth space with a series of co-axial cylinders, models the disparity estimation as a pixel-labelling problem and establishes an energy minimisation function for solving this problem using graph cuts optimisation. Based on the omni-stereo disparity-estimation results, the authors detect and track-moving objects based on omni-stereo disparity motion vector, which is the difference between two consecutive disparity maps. Experiments on moving car tracking justify the proposed method.

International audience; Image quality assessment (IQA) algorithms evaluate the perceptual quality of an image using evaluation scores that assess the similarity or difference between two images. We propose a new low-level feature-based IQA technique, which applies filter-bank decomposition and center-surround methodology. Differing from existing methods, our model incorporates color intensity adaptation and frequency scaling optimization at each filter-bank level and spatial orientation to extract and enhance perceptually significant features. Our computational model exploits the concept of object detection and encapsulates characteristics proposed in other IQA algorithms in a unified architecture. We also propose a systematic approach to review the evolution of IQA algorithms using unbiased test datasets, instead of looking at individual scores in isolation. Experimental results demonstrate the feasibility of our approach.

In this paper we describe a methodology for measuring the ground truth for boundary detection methods in medical images. An interface is used to allow medical experts to outline boundaries of interest on images. Following this, the accuracy of the experts in repeating the ground truth detection process is evaluated. Finally, an approach is described for comparing the ground truth as provided by experts with actual boundaries detected automatically. Experimental results are presented to validate the proposed algorithms.

International audience; This paper introduces a pneumatic haptic device to remotely control a slave ultrasound probe-holder robot. This device should orientate this probe according to the sonographer’s examination needs, while rendering the force applied by it on the patient’s body, in order to provide a realistic examination environment as in situ. Previous designs with electric actuators were limited in terms of torque, dimensions and ergonomics, which actually did not match end-users’ remote ultrasonography requirements. This paper describes the mechatronic design of an haptic pneumatic probe replica and preliminary control laws for it to perform as a Variable Stiffness Actuator (VSA). This approach is original and experimental results are provided to validate its feasibility.