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Owing to their large field of view, a catadioptric imaging system is widely used in several research areas, including robot navigation, surveillance, and three‐dimensional (3D) reconstruction. The modelling and calibration of these systems allow the accurate measurement of objects. This paper presents a calibration method for a panoramic 3D reconstruction system based on pattern projection composed of two modules. The first module, which contains a charged coupled device camera and a parabolic mirror allows the acquisition of catadioptric images. The second module is a catadioptric projection system made of a light projector and a parabolic mirror that generates a projected pattern over the target for reconstruction purposes. Both the modules are calibrated independently. The method achieves a reprojection error of 0.6 pixels in the camera module and 1.2 pixels in the catadioptric projection system. To evaluate the performance of the proposed method, the results show 3D reconstructions of multiple objects with tolerances around 1.3 mm. [ABSTRACT FROM AUTHOR]

Nonverbal communication is an intrinsic part in daily face-to-face meetings. A frequently observed behavior during social interactions is mirroring, in which one person tends to mimic the attitude of the counterpart. This paper shows that a computer vision system could be used to predict the perception of competence in dyadic interactions through the automatic detection of mirroring events. To prove our hypothesis, we developed: (1) A social assistant for mirroring detection, using a wearable device which includes a video camera and (2) an automatic classifier for the perception of competence, using the number of nodding gestures and mirroring events as predictors. For our study, we used a mixed-method approach in an experimental design where 48 participants acting as customers interacted with a confederated psychologist. We found that the number of nods or mirroring events has a significant influence on the perception of competence. Our results suggest that: (1) Customer mirroring is a better predictor than psychologist mirroring; (2) the number of psychologist's nods is a better predictor than the number of customer's nods; (3) except for the psychologist mirroring, the computer vision algorithm we used worked about equally well whether it was acquiring images from wearable smartglasses or fixed cameras. [ABSTRACT FROM PUBLISHER]

This paper introduces a tool for calibrating multiple Kinect V2 sensors. To achieve the calibration, at least three acquisitions are needed from each camera. The method uses the Kinect's coordinate mapping capabilities between the sensors to register data between camera, depth, and color spaces. The method uses a novel approach where it obtains multiple 3D points matches between adjacent sensors, and use them to estimating the camera parameters. Once the cameras are calibrated, the tool can perform point cloud fusion transforming all the 3D points to a single reference. We tested the system with a network of four Kinect V2 sensors and present calibration results. The tool is implemented in MATLAB using the Kinect for Windows SDK 2.0. [ABSTRACT FROM AUTHOR]

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Computing advances and increased smartphone use gives technology system designers greater flexibility in exploiting computer vision to support visually impaired users. Understanding these users' needs will certainly provide insight for the development of improved usability of computing devices. [ABSTRACT FROM PUBLISHER]

• Azure Kinect library for Python and Matlab. • Easy-to-use high-level functions to access Azure Kinect functionality. • Additional 32 hand keypoints to the existing 32 body keytpoints for tracking. This paper introduces KinZ , an Azure Kinect toolkit for Python and Matlab. This toolkit encapsulates the Azure Kinect's main functionality in an easy-to-use class with high-level methods. This software is written mostly in C/C++ with a pybind interface for Python and Mex functions for Matlab. It provides access to color, depth, infrared cameras, a mapping between cameras, colored point clouds, IMU sensor data, body tracking with 32 body joints plus 32 hand keypoints. We showed that KinZ applications could run in real-time at 1080p resolution, with the benefit of a high-level language reducing the learning curve and allowing a significant decrease in development time for prototyping and research. [ABSTRACT FROM AUTHOR]