Subject to the poor imaging quality of the infrared camera, the projector defocusing, and the subsurface scattering, the classical phase-shifting method is constrained for reconstructing three-dimensional (3D) face geometry. To address this issue, a face measurement method based on stripe edge detection using infrared light is proposed by designing the global codeword correction. Binary fringe instead of sinusoidal fringe is employed to resist the above disturbance. Significantly, an assistant fringe is developed according to the parity of the gray order, which then is utilized to generate the correction orders. Subsequently, the correction orders are employed to guide the decoding by the discriminator of the rising and falling edges in binary patterns. In this way, the 3D face without jump errors can be reconstructed using an infrared structured light system. Experiments verify the effectiveness of our method not only on the human face but also on the standard sphere and models.
A deep learning-based method is proposed to recover the absolute phase value from a single fringe pattern. We propose a deep neural network architecture that includes two subnetworks used for wrapping phase calculation and phase unwrapping, respectively. The training set is generated with the absolute phase obtained by the combination of phase shifting and gray coding. In addition, a reference plane is adopted to provide periodic range information for phase unwrapping. Then according to the output of the well-trained network, a high-quality absolute phase is obtained through only a single fringe pattern of the measured object. Experiments on the test set verify that high accuracy for complex texture objects is acquired using the proposed method, which indicates its potential in high-speed measurement.
3D Facial landmarking plays an important role on 3D face recognition and face expression recognition. However, the most of methods underperform when faces have occluded region such as hair, glasses or finger. To solve this problem, a coarseto-fine method is proposed, containing several denoising auto-encoder networks (denoted as DANs). DANs not only can recover the lost information but improve the accuracy of landmarking. Tests based on Bosphorus dataset show a 100% of good landmarking under 6mm precision of mean error, which demonstrates that our algorithm achieves the state-of-theart performance.
Stereo matching is an important and hot research topic in computer vision. In order to solve the well-known streaking effects of dynamic programming, and reduce the mismatch points on edges, discontinuous and textureless regions, we propose a cross-scale constrained dynamic programming algorithm for stereo matching. The algorithm involves both image pyramid model and Gaussian scale space to operate a coarse-to-fine dynamic programming on multi-scale cost volumes. For the purpose of improving the disparity accuracy in textureless region, a cross-scale regularized constraint is added to ensure the cost consistency, the computational burden is reduced by using the disparity estimation from lower scale operation to seed the search on the larger image. Both synthetic and real scene experimental results show our algorithm can effectively reduce the mismatch in textureless regions.
Targeting at 3D point cloud data without any foreknowledge of information, this paper presents a new algorithm of point cloud simplification. Because of usual way of shooting in daily life, there often exist more detailed information in x-y direction in the point cloud.By using this feature, the proposed algorithm firstly selects x-y axis as the direction for division and computation and obtains x-y boundary. After observation of normal vector of point cloud, it is easy to find that if the normal vector of the points in the local region changes gently, it indicates that the region is relatively flat. On the contrary, if the normal vector changes greatly, it indicates that the region fluctuates greatly. Therefore, compute the arithmetic mean of the included angle between the normal vector of one point in the point cloud and the normal vector of its k-neighborhood point. Define the feature of that point, and based on this, extract key feature points in data. Finally, the gridding method is used to divide the scattered point cloud data whose boundary and key points have been extracted and thus finish simplification. Experimental results show the effectiveness of the proposed algorithm.
Empirical mode decomposition (EMD) based methods have been widely used in fringe pattern analysis, including denoising, detrending, normalization, etc. The common problem of using EMD and Bi-dimensional EMD is the mode mixing problem, which is generally caused by uneven distribution of extrema. In recent years, we have proposed some algorithms to solve the mode mixing problem and further applied these methods in fringe analysis. In this paper, we introduce the development of these methods and show the successful results of two most recent algorithms.
Rod-dominated transient retinal phototropism (TRP) has been recently observed in freshly isolated mouse and frog retinas. Comparative confocal microscopy and optical coherence tomography revealed that the TRP was predominantly elicited from the rod outer segment (OS). However, the biophysical mechanism of rod OS dynamics is still unknown. Mouse and frog retinal slices, which displayed a cross-section of retinal photoreceptors and other functional layers, were used to test the effect of light stimulation on rod OSs. Time-lapse microscopy revealed stimulus-evoked conformational changes of rod OSs. In the center of the stimulated region, the length of the rod OS shrunk, while in the peripheral region, the rod OS swung toward the center region. Our experimental observation and theoretical analysis suggest that the TRP may reflect unbalanced rod disc-shape changes due to localized visible light stimulation.
Oblique light stimulation evoked transient retinal phototropism (TRP) has been recently detected in frog and mouse retinas. High resolution microscopy of freshly isolated retinas indicated that the TRP is predominated by rod photoreceptors. Comparative confocal microscopy and optical coherence tomography (OCT) revealed that the TRP predominantly occurred from the photoreceptor outer segment (OS). However, biophysical mechanism of rod OS change is still unknown. In this study, frog retinal slices, which open a cross section of retinal photoreceptor and other functional layers, were used to test the effect of light stimulation on rod OS. Near infrared light microscopy was employed to monitor photoreceptor changes in retinal slices stimulated by a rectangular-shaped visible light flash. Rapid rod OS length change was observed after the stimulation delivery. The magnitude and direction of the rod OS change varied with the position of the rods within the stimulated area. In the center of stimulated region the length of the rod OS shrunk, while in the peripheral region the rod OS tip swung towards center region in the plane perpendicular to the incident stimulus light. Our experimental result and theoretical analysis suggest that the observed TRP may reflect unbalanced disc-shape change due to localized pigment bleaching. Further investigation is required to understand biochemical mechanism of the observed rod OS kinetics. Better study of the TRP may provide a noninvasive biomarker to enable early detection of age-related macular degeneration (AMD) and other diseases that are known to produce retinal photoreceptor dysfunctions.
The code analysis of the fringe image is playing a vital role in the data acquisition of structured light systems, which
affects precision, computational speed and reliability of the measurement processing. According to the self-normalizing
characteristic, a fringe image processing method based on structured light is proposed. In this method, a series of
projective patterns is used when detecting the fringe order of the image pixels. The structured light system geometry is
presented, which consist of a white light projector and a digital camera, the former projects sinusoidal fringe patterns
upon the object, and the latter acquires the fringe patterns that are deformed by the object's shape. Then the binary
images with distinct white and black strips can be obtained and the ability to resist image noise is improved greatly. The
proposed method can be implemented easily and applied for profile measurement based on special binary code in a wide
field.
A measurement system based on projected fringe model is presented. In this model, the location of fringe strips is determined by the image patterns on the projection plane directly, and the relationship between object point and its image point is established to obtain the coordinates of surface point. It is unnecessary to arrange the system in parallel, while the camera and projector can be in arbitrary position. Experiments show that the surface measurement system is applicable to many shape measurement tasks.
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