Graduate School of Electronics Engineering

This article describes the 3D handheld profiling system composed of a stereo camera and an illumination projector to collect high-resolution data for close range of applications. Visual navigation approach is either based on feature matching or on accurate target, and the target-based approach was found to be more accurate if the 3D object has less texture on its surface. Block matching algorithm was used to render the single-view 3D reconstruction. For multiview 3D modeling, coarse registration and final refinement of the point clouds using iterative closest point algorithm were utilized. The proposed approach yields good accuracy for multiview registration as demonstrated in the results of this research.

This paper surveys zoom-lens calibration approaches, such as pattern-based calibration, self-calibration, and hybrid (or semiautomatic) calibration. We describe the characteristics and applications of various calibration methods employed in zoom-lens calibration and offer a novel classification model for zoom-lens calibration approaches in both single and stereo cameras. We elaborate on these calibration techniques to discuss their common characteristics and attributes. Finally, we present a comparative analysis of zoom-lens calibration approaches, highlighting the advantages and disadvantages of each approach. Furthermore, we compare the linear and nonlinear camera models proposed for zoom-lens calibration and enlist the different techniques used to model the camera's parameters for zoom (or focus) settings.

This paper describes the implementation of a 3D handheld scanning system based on visual inertial pose estimation and structured light technique.3D scanning system is composed of stereo camera, inertial navigation system (INS) and illumination projector to collect high resolution data for close range applications. The proposed algorithm for visual pose estimation is either based on feature matching or using accurate target object. The integration of INS enables the scanning system to provide the fast and reliable pose estimation supporting visual pose estimates. Block matching algorithm was used to render two view 3D reconstruction. For multiview 3D approach, rough registration and final alignment of point clouds using iterative closest point algorithm further improves the scanning accuracy. The proposed system is potentially advantageous for the generation of 3D models in bio-medical applications.

In this paper, the design and implementation of a 3D sensing system with adjustable zoom based on stereo vision and structured light is discussed. The proposed system consists of a stereo camera with an illumination projector and zoom lenses to collect high-resolution data from a distant object. A calibration target suitable for zoom lens calibration is designed along with the development of a zoom lens calibration method for a stereo camera based on linear and non-linear models. The robust zoom lens control system, based on a precise automation hardware and image processing technique, is developed to produce high-quality images. Furthermore, normalized cross correlation (NCC), being robust with intensity offsets and contrast changes, is used for stereo matching of the coded images to generate the reconstruction results using a linear equation method. The integration of NCC with structured light and epipolar geometry for the proposed 3D sensing system further yields accurate 3D reconstruction results as demonstrated in the experimental results of this research. The complex relationship of the parameters of each camera on variable zoom is determined using optimal fitting. Linear interpolation is used to estimate calibration data at an arbitrary zoom setting to validate zoom lens calibration. The 3D reconstruction on variable zoom shows that higher lens magnification results in a more accurate 3D sensing system.

When 3d image registration using 2d image by hand-held scanner, the most important thing is pose estimation and object surface measure. The relationship between images is important to image registration. In this paper suggest 3d registration using Kinect and INS. The Kinect and INS are integrated on rigid body to improve the accuracy of estimate pose. It can complement the disadvantages of each sensor through the sensor fusion of INS and vision sensor position to make more precise estimates. Using purposed system can measure the three-dimensional shape of a variety of objects, and also can obtain an accurate image in a medical imaging applications which require precision application and apply in Image-guided surgery.

In this article, a multi-view registration approach for the 3D handheld profiling system based on the multiple shot structured light technique is proposed. The multi-view registration approach is categorized into coarse registration and point cloud refinement using the iterative closest point (ICP) algorithm. Coarse registration of multiple point clouds was performed using relative orientation and translation parameters estimated via homography-based visual navigation. The proposed system was evaluated using an artificial human skull and a paper box object. For the quantitative evaluation of the accuracy of a single 3D scan, a paper box was reconstructed, and the mean errors in its height and breadth were found to be 9.4 µm and 23 µm, respectively. A comprehensive quantitative evaluation and comparison of proposed algorithm was performed with other variants of ICP. The root mean square error for the ICP algorithm to register a pair of point clouds of the skull object was also found to be less than 1 mm.

Video display content can be extended to the walls of the living room around the TV using projection. The problem of providing appropriate projection content is hard for the computer and we solve this problem with deep neural network. We propose the peripheral vision system that provides the immersive visual experiences to the user by extending the video content using deep learning and projecting that content around the TV screen. The user may manually create the appropriate content for the existing TV screen, but it is too expensive to create it. The PCE (Pixel context encoder) network considers the center of the video frame as input and the outside area as output to extend the content using supervised learning. The proposed system is expected to pave a new road to the home appliance industry, transforming the living room into the new immersive experience platform.

The state of the art techniques used by medical practitioners to extract the three-dimensional (3D) geometry of different body parts requires a series of images/frames such as laser line profiling or structured light scanning. Movement of the patients during scanning process often leads to inaccurate measurements due to sequential image acquisition. Single shot structured techniques are robust to motion but the prevalent challenges in single shot structured light methods are the low density and algorithm complexity. In this research, a single shot 3D measurement system is presented that extracts the 3D point cloud of human skin by projecting a laser speckle pattern using a single pair of images captured by two synchronized cameras. In contrast to conventional laser speckle 3D measurement systems that realize stereo correspondence by digital correlation of projected speckle patterns, the proposed system employs KLT tracking method to locate the corresponding points. The 3D point cloud contains no outliers and sufficient quality of 3D reconstruction is achieved. The 3D shape acquisition of human body parts validates the potential application of the proposed system in the medical industry.

We propose the system that provides an immersive experience by automatically extending the video content of the TV to the wall. Though it is possible to manually create the appropriate content that works on the existing TV screen, the cost is too expensive to create. The proposed deep neural network uses the center of the video as input and the outside area as output. The trained network automatically generates the extrapolated video according to the input video and a projector projects the resulting content on the living room wall around the TV thereby improving the immersive feeling. The proposed system is expected to pave a new road to the home appliance industry by transforming the living room into the new immersive experience platform.

To a great extent, Pakistan and Turkey rely on imported fossil fuels to meet their energy demands. Pakistan is moving in the right direction, placing focus on renewable energy resources in its current infrastructure in order to address the energy shortage. Several projects (e.g., wind power and solar PV (photovoltaic) technologies) are operational or under development; they are intended to reduce energy challenges in Pakistan. The new government in Pakistan aims to increase the share of renewable energy in total power generation to 30% by 2030. On the other hand, Turkey surpasses Pakistan in renewable energy resources; for example, there are 186 operational wind energy power plants across the country. In addition, Turkey utilizes solar energy—mainly for residential usage. Turkey’s Vision 2023 energy agenda aims to supply 30% of their power demands from modern renewable energy resources. Turkey has implemented solar PV, solar buildings, wind power plants, geothermal energy resources,...

Forecasting the microeconomics of electricity will turn into a challenging process when electricity is produced through renewable energy technologies (RET). These technologies are mainly sunlight-based photovoltaic (PV), wind power, and tidal resources, which vigorously rely upon ecological conditions. For a reliable and livable energy supply to the electricity grid from renewable means, electrical energy storage technologies can play an important role while considering the weather effects in order to provide immaculate, safe, and continuous energy throughout the generation period. Energy storage technologies (ESTs) charge themselves during the low power demand period and discharge when the demand of electricity increases in such a way that they act as a catalyst to provide energy boost to the power grid. In this paper, we presented and discussed the renewable ESTs for each type with respect to their operational mechanism. In this regard, the renewable energy scenarios of Pakistan a...

In this article, a multi-view registration approach for the 3D handheld profiling system based on the multiple shot structured light technique is proposed. The multi-view registration approach is categorized into coarse registration and point cloud refinement using the iterative closest point (ICP) algorithm. Coarse registration of multiple point clouds was performed using relative orientation and translation parameters estimated via homography-based visual navigation. The proposed system was evaluated using an artificial human skull and a paper box object. For the quantitative evaluation of the accuracy of a single 3D scan, a paper box was reconstructed, and the mean errors in its height and breadth were found to be 9.4 μm and 23 μm, respectively. A comprehensive quantitative evaluation and comparison of proposed algorithm was performed with other variants of ICP. The root mean square error for the ICP algorithm to register a pair of point clouds of the skull object was also found ...