• Fashion & Textile Research Journal
• /
• v.24 no.6
• /
• pp.812-824
• /
• 2022

This study proposes to develop a 3D printed re-entrant(RE) strip by shape memory thermoplastic polyurethane that can be deformed and recovered by thermal stimulation. The most suitable 3D printing infill density condition and temperature condition during shape recovery for mechanical behavior were confirmed. As the poisson's ratio indicated, the higher the recovery temperature, the closer the poisson's ratio to zero and the better the auxetic properties. After recovery testing for five minutes, it appeared that the shape recovery ratio was the highest at 70℃. The temperature range when the shape recovery ratio appeared to be more than 90% was a recovery temperature of more than 50℃ and 60℃ when deformed under a constant load of 100 gf and 300 gf, respectively. This indicated that further deformation occurred after maximum recovery when recovered at a temperature of 80℃, which is above the glass transition temperature range. As for REstrip by infill density, a shape recovery properties of 100% was superior than 50%. Additionally, as the re-entrant structure exhibited a shape recovery ratio of more than 90%, and exhibited auxetic properties. It was confirmed that the infill density condition of 100% and the temperature condition of 70℃ are suitable for REstrips for applying the actuator.

• Journal of the Semiconductor & Display Technology
• /
• v.12 no.2
• /
• pp.27-32
• /
• 2013

Shape From Focus (SFF) is a passive optical technique to recover 3D structure of an object that utilizes focus information from 2D images of the object taken at different focus levels. Mostly, SFF methods use a single focus measure to compute image focus quality of each pixel in the image sequence. However, it is difficult to recover accurate 3D shape using a single focus measure, as different focus measures perform differently in diverse conditions. In this paper, a nonlinear Total Variation (TV) based approach is proposed for 3D shape recovery. To improve the result of surface reconstruction, several initial depth maps are obtained using different focus measures and the resultant 3D shape is obtained by diffusing them through TV. The proposed method is tested and evaluated by using image sequences of synthetic and real objects. The results and comparative analysis demonstrate the effectiveness of our method.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.33B no.6
• /
• pp.73-81
• /
• 1996

In this paper, based on the constrained optimizatin technique and direct recovery method, we proesent a shape form shading (SFS) algorithm to recover a 3-D shape form an image. More specifically, we first employ the membrane model for a smoothness constraint to revoer a 3-D shape coarsely. We then compute the surface height directly to reduce the shape distortion due to a regularization term. In our approach, we can obtain a stable and accurate solution by the application of these two steps. Several simulation results on various images are provided and discussed in this paper and they show that the proposed algorithm extracts the 3-D information accurately and efficiently.

• Journal of the Semiconductor & Display Technology
• /
• v.11 no.3
• /
• pp.19-25
• /
• 2012

The accuracy of Shape From Focus (SFF) technique depends on the quality of the focus measurements which are computed through a focus measure operator. In this paper, we introduce a new approach to estimate 3D shape of an object based on Gaussian process regression. First, initial depth is estimated by applying a conventional focus measure on image sequence and maximizing it in the optical direction. In second step, input feature vectors consisting of eginvalues are computed from 3D neighborhood around the initial depth. Finally, by utilizing these features, a latent function is developed through Gaussian process regression to estimate accurate depth. The proposed approach takes advantages of the multivariate statistical features and covariance function. The proposed method is tested by using image sequences of various objects. Experimental results demonstrate the efficacy of the proposed scheme.

• The KIPS Transactions:PartB
• /
• v.10B no.2
• /
• pp.135-142
• /
• 2003

Robust extraction of 3D object's features, shape and global motion information from 2D image sequence is described. The object's 21 feature points on the pyramid type synthetic object are extracted automatically using color transform technique. The extracted features are used to recover the 3D shape and global motion of the object using stereo paraperspective camera model and sequential SVD(Singuiar Value Decomposition) factorization method. An inherent error of depth recovery due to the paraperspective camera model was removed by using the stereo image analysis. A 30 synthetic object with 21 features reflecting various position was designed and tested to show the performance of proposed algorithm by comparing the recovered shape and motion data with the measured values.

• Journal of Korea Multimedia Society
• /
• v.10 no.3
• /
• pp.303-315
• /
• 2007

This paper proposes a 3D structure recovery and registration method that uses four or more common points. For each frame of a given video, a partial structure is recovered using tracked points. The 3D coordinates, camera positions and camera directions are computed at once by our improved scaled orthographic factorization method. The partially recovered point sets are parts of a whole model. A registration of point sets makes the complete shape. The recovered subsets are integrated by transforming each coordinate system of the local point subset into a common basis coordinate system. The process of shape recovery and integration is performed uniformly and linearly without any nonlinear iterative process and without loss of accuracy. The execution time for the integration is significantly reduced relative to the conventional ICP method. Due to the fast recovery and registration framework, our shape recovery scheme is applicable to various interactive video applications. The processing time per frame is under 0.01 seconds in most cases and the integration error is under 0.1mm on average.

• Current Optics and Photonics
• /
• v.4 no.5
• /
• pp.411-420
• /
• 2020

Non-contact three-dimensional (3D) measuring technology is used to identify defects in miniature products, such as optics, polymers, and semiconductors. Hence, this technology has garnered significant attention in computer vision research. In this paper, we focus on shape from focus (SFF), which is an optical passive method for 3D shape recovery. In existing SFF techniques using interpolation, all datasets of the focus volume are approximated using one model. However, these methods cannot demonstrate how a predefined model fits all image points of an object. Moreover, it is not reasonable to explain various shapes of datasets using one model. Furthermore, if noise is present in the dataset, an error will be generated. Therefore, we propose an algorithm based on polynomial regression analysis to address these disadvantages. Our experimental results indicate that the proposed method is more accurate than existing methods.

• KIPS Transactions on Software and Data Engineering
• /
• v.6 no.1
• /
• pp.23-28
• /
• 2017

Shape from focus (SFF) is a technique used to reconstruct 3D shape of objects from a sequence of images obtained at different focus settings of the lens. In this paper, a new shape from focus method for 3D reconstruction of microscopic objects is described, which is based on gradient operator in Mathematical Morphology. Conventionally, in SFF methods, a single focus measure is used for measuring the focus quality. Due to the complex shape and texture of microscopic objects, single measure based operators are not sufficient, so we propose morphological operators with multi-structuring elements for computing the focus values. Finally, an optimal focus measure is obtained by combining the response of all focus measures. The experimental results showed that the proposed algorithm has provided more accurate depth maps than the existing methods in terms of three-dimensional shape recovery.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.20 no.2
• /
• pp.281-288
• /
• 2016

The natural moving objects are the most non-rigid shapes with randomly time-varying deformation, and its types also very diverse. Methods of non-rigid shape reconstruction have widely applied in field of movie or game industry in recent years. However, a realistic approach requires moving object to stick many beacon sets. To resolve this drawback, non-rigid shape reconstruction researches from input video without beacon sets are investigated in multimedia application fields. In this regard, our paper propose novel CPSRF(Chained Partial Stereo Rigid Factorization) algorithm that can reconstruct a non-rigid 3D shape. Our method is focused on the real-time reconstruction of non-rigid 3D shape and motion from stereo 2D video sequences per frame. And we do not constrain that the deformation of the time-varying non-rigid shape is limited by a Gaussian distribution. The experimental results show that the 3D reconstruction performance of the proposed CPSRF method is superior to that of the previous method which does not consider the random deformation of shape.

• Journal of the Korean Society for Heat Treatment
• /
• v.37 no.2
• /
• pp.79-85
• /
• 2024

The effects of annealing heat treatment and the addition of Cu element on the shape memory effect of the NiTi-based alloy were investigated by analyzing differential scanning calorimeter results and characterizing recovery rate through 3D scanning after Vickers hardness test. Through 3D scanning of impressions after Vickers hardness test, the strain recovery rates for specimens without annealing treatment and annealed specimens at 400, 450, and 500℃ were measured as 45.96%, 46.76%, 52.37%, and 43.57%, respectively. This is because as the annealing temperature increases, both B19' and NiTi₂ phases, which can impede martensitic transformation, are incorporated within the NiTi matrix. Particularly, additional phase transformation from R-phase to B19' observed in specimens annealed at 400 and 450℃ significantly contributes to the improvement in strain recovery rates. Additionally, the results regarding the Cu element content indicate that when the total content of Ni and Cu is below 49.6 at.%, the precipitation of fine B19' and NiTi₂ phases within the matrix can greatly influence the transformation enthalpy and temperature range, resulting in relatively lower strain recovery rates in NiTi alloys with a small amount of Cu element produced in this study.