Rich Structural Index for Stereoscopic Image Quality Assessment

The human visual system (HVS), affected by viewing distance when perceiving the stereo image information, is of great significance to study of stereoscopic image quality assessment. Many methods of stereoscopic image quality assessment do not have comprehensive consideration for human visual perception characteristics. In accordance with this, we propose a Rich Structural Index (RSI) for Stereoscopic Image objective Quality Assessment (SIQA) method based on multi-scale perception characteristics. To begin with, we put the stereo pair into the image pyramid based on Contrast Sensitivity Function (CSF) to obtain sensitive images of different resolution . Then, we obtain local Luminance and Structural Index (LSI) in a locally adaptive manner on gradient maps which consider the luminance masking and contrast masking. At the same time we use Singular Value Decomposition (SVD) to obtain the Sharpness and Intrinsic Structural Index (SISI) to effectively capture the changes introduced in the image (due to distortion). Meanwhile, considering the disparity edge structures, we use gradient cross-mapping algorithm to obtain Depth Texture Structural Index (DTSI). After that, we apply the standard deviation method for the above results to obtain contrast index of reference and distortion components. Finally, for the loss caused by the randomness of the parameters, we use Support Vector Machine Regression based on Genetic Algorithm (GA-SVR) training to obtain the final quality score. We conducted a comprehensive evaluation with state-of-the-art methods on four open databases. The experimental results show that the proposed method has stable performance and strong competitive advantage.

Development of laboratory devices for real-time measurement of object 3D position using stereo cameras

Measuring the 3D position at any time of a given object in real-time automatically and well documented to understand a physical phenomenon is essential. Exploring a stereo camera in developing 3D images is very intriguing since a 3D image perception generated by a stereo image may be reprojected back to generate a 3D object position at a specific time. This research aimed to develop a device and measure the 3D object position in real-time using a stereo camera. The device was constructed from a stereo camera, tripod, and a mini-PC. Calibration was carried out for position measurement in X, Y, and Z directions based on the disparity in the two images. Then, a simple 3D position measurement was carried out based on the calibration results. Also, whether the measurement was in real-time was justified. By applying template matching and triangulation algorithms on those two images, the object position in the 3D coordinate was calculated and recorded automatically. The disparity resolution characteristic of the stereo camera was obtained varied from 132 pixels to 58 pixels for an object distance to the camera from 30 cm to 70 cm. This setup could measure the 3D object position in real-time with an average delay time of less than 50 ms, using a notebook and a mini-PC. The 3D position measurement can be performed in real-time along with automatic documentation. Upon the stereo camera specifications used in this experiment, the maximum accuracy of the measurement in X, Y, and Z directions are ΔX = 0.6 cm, ΔY = 0.2 cm, and ΔZ = 0.8 cm at the measurement range of 30 cm–60 cm. This research is expected to provide new insights in the development of laboratory tools for learning physics, especially mechanics in schools and colleges.

Urban Building Mesh Polygonization Based on 1-Ring Patch and Topology Optimization

With the development of UAV and oblique photogrammetry technology, the multi-view stereo image has become an important data source for 3D urban reconstruction, and the surface meshes generated by it have become a common way to represent the building surface model due to their high geometric similarity and high shape representation ability. However, due to the problem of data quality and lack of building structure information in multi-view stereo image data sources, it is a huge challenge to generate simplified polygonal models from building surface meshes with high data redundancy and fuzzy structural boundaries, along with high time consumption, low accuracy, and poor robustness. In this paper, an improved mesh representation strategy based on 1-ring patches is proposed, and the topology validity is improved on this basis. Experimental results show that our method can reconstruct the concise, manifold, and watertight surface models of different buildings, and it can improve the processing efficiency, parameter adaptability, and model quality.

Research on relative orientation method of oblique aerial photography based on basic matrix

After the oblique aerial photography technology is used to collect the stereo image, it is necessary to use the relative orientation method to check the image parameters. After the rectification process is completed, the 3D software is used to draw the 3D model to meet the subsequent application requirements. The author of this paper analyzes the difficulty of the matching and aerial photography, including affine transformation cannot successful transformation, influence there covered phenomenon and characteristic finishing is difficult, the combination of fundamental matrix tilt aerial photography as a method of relative orientation, through the study of oblique aerial photography based matrix as precision control points, its aim is to continuously optimize tilt aerial photography as the content, improve the use value of collation results.

Real-Time FPGA Accelerated Stereo Matching for Temporal Statistical Pattern Projector Systems

The presented paper describes a hardware-accelerated field programmable gate array (FPGA)–based solution capable of real-time stereo matching for temporal statistical pattern projector systems. Modern 3D measurement systems have seen an increased use of temporal statistical pattern projectors as their active illumination source. The use of temporal statistical patterns in stereo vision systems includes the advantage of not requiring information about pattern characteristics, enabling a simplified projector design. Stereo-matching algorithms used in such systems rely on the locally unique temporal changes in brightness to establish a pixel correspondence between the stereo image pair. Finding the temporal correspondence between individual pixels in temporal image pairs is computationally expensive, requiring GPU-based solutions to achieve real-time calculation. By leveraging a high-level synthesis approach, matching cost simplification, and FPGA-specific design optimizations, an energy-efficient, high throughput stereo-matching solution was developed. The design is capable of calculating disparity images on a 1024 × 1024(@291 FPS) input image pair stream at 8.1 W on an embedded FPGA platform (ZC706). Several different design configurations were tested, evaluating device utilization, throughput, power consumption, and performance-per-watt. The average performance-per-watt of the FPGA solution was two times higher than in a GPU-based solution.