Local Stereo Research Articles

PaCh (Packed Chemicals): Computationally Effective Binary Format for Chemical Structure Encoding.

In this work, we propose a versatile molecule and reaction encoding binary data format that aims to bridge the gap between the advantages of SMILES, like local stereo- and implicit hydrogen encoding, and block-structured MDL MOL with a 2D layout and explicit bond encoding, while addressing their respective limitations. Our new format introduces a balance between size efficiency, processing speed, and comprehensive representation, making it well-suited for various applications in cheminformatics, including deep learning, data storage, and searching. By offering an explicit approach to store atom connectivity (including implicit hydrogens), electronic state, stereochemistry, and other crucial molecular attributes, our proposal seeks to enhance data storage efficiency and promote interoperability among different software tools.

3D Vision System for a Robotic Arm Based on Equal Baseline Camera Array

This paper presents a lightweight 3D vision system called Equal Baseline Camera Array (EBCA). EBCA can work in different light conditions and it can be applied for measuring large range of distances. The system is a useful alternative to other known distance measuring devices such as structured-light 3D scanners, time-of-flight cameras, Light Detection and Ranging (LIDAR) devices and structure from motion techniques. EBCA can be mounted on a robotic arm without putting significant load on its construction. EBCA consists of a central camera and a ring of side cameras. The system uses stereo matching algorithms to acquire disparity maps and depth maps similarly as in case of using stereo cameras. This paper introduces methods of adapting stereo matching algorithms designed for stereo cameras to EBCA. The paper also presents the analysis of local, semi-global and global stereo matching algorithms in the context of the EBCA usage. Experiments show that, on average, results obtained from EBCA contain 37.49% less errors than the results acquired from a single stereo camera used in the same conditions.

Local iterative DLT soft-computing vs. interval-valued stereo calibration and triangulation with uncertainty bounding in 3D reconstruction

The use of stereo vision for 3D data gathering is affected by constraints in the position of the cameras, the quality of the optical elements and the numerical algorithms for calibration and matching. Also, there is not a wide agreement on the best procedure for bounding the 3D errors within an uncertainty volume. In this work, this problem is solved by implementing the whole set of computations, including calibration and triangulation, with interval data. This is in contrast with previous works that rely on Direct Linear Transform (DLT) as a camera model. To keep better with real lens aberrations, a local iterative modification is proposed that provides an on-demand set of calibration parameters for each 3D point, comprising those nearest in 3D space. In this way, the estimated camera parameters are closely related with camera aberrations at the lens area through which that 3D point is imaged. To further reduce the triangulation uncertainty volume, a Soft Computing approach is proposed that represents each 3D point uncertainty as a cloud of crisp points compatible with interval-valued calibration data.Real data from previous works in related research areas is used to judge whether the new approach improves the precision and accuracy of other crisp and interval-valued estimations without degrading precision, and it is concluded that the new technique is able to significantly improve the uncertainty volumes.

The Implementation of Parallel Speed up Stereo Matching Based on Reduced Graph Cuts

The Many stereo matching problems can be converted to energy minimization problem, by establishment of special network graph to obtain the minimum graph cut, and then obtaining the optimal solution. For graph cuts algorithm, complete network graph include all vertices and disparity edges, the computation of time and space is huge. In this paper, we put forward a method by combing local and global stereo matching, set up a reduced network graph by the possible disparities values for each pixel, and then global optimization, to slove the maximum flow polynomial through CUDA parallel computing, greatly reduced the consumption of time and space.

A Pilot Study of Video Compression Techniques for Stereoscopic Telepresence Applications

This paper focuses on evaluating and quantifying the effects of a novel foveated stereo video compression algorithm for visual telepresence applications. In a typical telepresence application, a user at the local site views real-time stereo video captured and transmitted from a telerobotic camera platform located at a remote site. The telerobotic camera platform tracks the user's head motion, producing the sensation of being present at the remote site. Three valuable factors were examined: foveation, disparity compression, and global motion compensation. The algorithm was analyzed by introducing the above-mentioned components separately. It was found that each component increased the compression rate significantly.