Generating 3D models of objects using multiple visual cues in image sequences

Author(s):  
Jiang Yu Zheng ◽  
Akio Murata ◽  
Norihiro Abe
2011 ◽  
Vol 317-319 ◽  
pp. 843-846
Author(s):  
Sheng Yong Chen ◽  
Da Wei Liu ◽  
Xiao Yan Wang ◽  
Wei Huang ◽  
Qiu Guan

For acquisition of complete 3D models, this paper uses a rotational device to capture a set of image sequences. A direct projective reconstruction method is proposed by linear transformation, which can avoid getting corresponding points in more than two images. Actually, projective reconstructions are obtained from two neighboring images and the reconstructions are combined with the common 3D points. Finally, all reconstructions are merged into the initial one to construct a complete model. Several practical experiments have been carried out to validate the accuracy of the method.


1997 ◽  
Vol 9 (2) ◽  
pp. 125-135 ◽  
Author(s):  
Sotiris Malassiotis ◽  
Michael G. Strintzis

Author(s):  
Shilin Wang ◽  
Alan Wee-Chung Liew

In recent years, there is a growing interest in using visual information for automatic lipreading (Kaynak, Zhi, Cheok, Sengupta, Jian, & Chung, 2004) and visual speaker authentication (Mok, Lau, Leung, Wang, & Yan, 2004). It has been shown that visual cues, such as lip shape and lip movement, would greatly improve the performance of these systems. Various techniques have been proposed in the past decades to extract speech/speaker relevant information from lip image sequences. One approach is to extract the lip contour from lip image sequences. This generally involves lip region segmentation and lip contour modeling (Liew, Leung, & Lau, 2002; Wang, Lau, Leung, & ALiew, 2004), and the performance of the visual speech recognition and visual speaker authentication systems depends much on the accuracy and efficiency of these two procedures. Lip region segmentation aims to label the pixels in the lip image into lip and non-lip. The accuracy and robustness of the lip segmentation process is of vital importance for subsequent lip extraction. However, large variations caused by different speakers, lighting condition, or make-ups make the task difficult. The low color contrast between lip and facial skin, and the presence of facial hair, further complicate the problem. Given a correctly segmented lip region, the lip extraction process then involves fitting a lip model to the lip region. A good lip model should be compact, that is, with a small number of parameters, and should adequately represent most valid lip shapes while rejecting most invalid shapes. As most lip extraction techniques involve iterative model fitting, the efficiency of the optimization process is another important issue.


2018 ◽  
Vol 159 (5) ◽  
pp. 933-937 ◽  
Author(s):  
Samuel R. Barber ◽  
Saurabh Jain ◽  
Young-Jun Son ◽  
Eugene H. Chang

The surgeon’s knowledge of a patient’s individual anatomy is critical in skull base surgery. Trainees and experienced surgeons can benefit from surgical simulation; however, current models are expensive and impractical for widespread use. In this study, we report a next-generation mixed-reality surgical simulator. We segmented critical anatomic structures for 3-dimensional (3D) models to develop a modular teaching tool. We then developed a navigation tracking system utilizing a 3D-printed endoscope as a trackable virtual-reality (VR) controller and validated the accuracy on VR and 3D-printed skull models within 1 cm. We combined VR and augmented-reality visual cues with our 3D physical model to simulate sinus endoscopy and highlight segmented structures in real time. This report provides evidence that a mixed-reality simulator combining VR and 3D-printed models is feasible and may prove useful as an educational tool that is low cost and customizable.


2004 ◽  
Vol 13 (2) ◽  
pp. 222-233 ◽  
Author(s):  
Ulrich Neumann ◽  
Suya You ◽  
Jinhui Hu ◽  
Bolan Jiang ◽  
Ismail Oner Sebe

An Augmented Virtual Environment (AVE) fuses dynamic imagery with 3D models. An AVE provides a unique approach to visualizing spatial relationships and temporal events that occur in real-world environments. A geometric scene model provides a 3D substrate for the visualization of multiple image sequences gathered by fixed or moving image sensors. The resulting visualization is that of a world-in-miniature that depicts the corresponding real-world scene and dynamic activities. This paper describes the core elements of an AVE system, including static and dynamic model construction, sensor tracking, and image projection for 3D visualization.


2014 ◽  
Vol 23 (3) ◽  
pp. 132-139 ◽  
Author(s):  
Lauren Zubow ◽  
Richard Hurtig

Children with Rett Syndrome (RS) are reported to use multiple modalities to communicate although their intentionality is often questioned (Bartolotta, Zipp, Simpkins, & Glazewski, 2011; Hetzroni & Rubin, 2006; Sigafoos et al., 2000; Sigafoos, Woodyatt, Tuckeer, Roberts-Pennell, & Pittendreigh, 2000). This paper will present results of a study analyzing the unconventional vocalizations of a child with RS. The primary research question addresses the ability of familiar and unfamiliar listeners to interpret unconventional vocalizations as “yes” or “no” responses. This paper will also address the acoustic analysis and perceptual judgments of these vocalizations. Pre-recorded isolated vocalizations of “yes” and “no” were presented to 5 listeners (mother, father, 1 unfamiliar, and 2 familiar clinicians) and the listeners were asked to rate the vocalizations as either “yes” or “no.” The ratings were compared to the original identification made by the child's mother during the face-to-face interaction from which the samples were drawn. Findings of this study suggest, in this case, the child's vocalizations were intentional and could be interpreted by familiar and unfamiliar listeners as either “yes” or “no” without contextual or visual cues. The results suggest that communication partners should be trained to attend to eye-gaze and vocalizations to ensure the child's intended choice is accurately understood.


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