Extrinsic Infrastructure Calibration Using the Hand-Eye Robot-World Formulation

We propose a certifiably globally optimal approach for solving the hand-eye robot-world problem supporting multiple sensors and targets at once. Further, we leverage this formulation for estimating a geo-referenced calibration of infrastructure sensors. Since vehicle motion recorded by infrastructure sensors is mostly planar, obtaining a unique solution for the respective hand-eye robot-world problem is unfeasible without incorporating additional knowledge. Hence, we extend our proposed method to include a-priori knowledge, i.e., the translation norm of calibration targets, to yield a unique solution. Our approach achieves state-of-the-art results on simulated and real-world data. Especially on real-world intersection data, our approach utilizing the translation norm is the only method providing accurate results.Comment: Accepted at 2023 IEEE Intelligent Vehicles Symposiu

Putting culture under the spotlight reveals universal information use for face recognition

Background: Eye movement strategies employed by humans to identify conspecifics are not universal. Westerners predominantly fixate the eyes during face recognition, whereas Easterners more the nose region, yet recognition accuracy is comparable. However, natural fixations do not unequivocally represent information extraction. So the question of whether humans universally use identical facial information to recognize faces remains unresolved. Methodology/Principal Findings: We monitored eye movements during face recognition of Western Caucasian (WC) and East Asian (EA) observers with a novel technique in face recognition that parametrically restricts information outside central vision. We used ‘Spotlights’ with Gaussian apertures of 2°, 5° or 8° dynamically centered on observers’ fixations. Strikingly, in constrained Spotlight conditions (2°, 5°) observers of both cultures actively fixated the same facial information: the eyes and mouth. When information from both eyes and mouth was simultaneously available when fixating the nose (8°), as expected EA observers shifted their fixations towards this region. Conclusions/Significance: Social experience and cultural factors shape the strategies used to extract information from faces, but these results suggest that external forces do not modulate information use. Human beings rely on identical facial information to recognize conspecifics, a universal law that might be dictated by the evolutionary constraints of nature and not nurture

Culture shapes how we look at faces

Background: Face processing, amongst many basic visual skills, is thought to be invariant across all humans. From as early as 1965, studies of eye movements have consistently revealed a systematic triangular sequence of fixations over the eyes and the mouth, suggesting that faces elicit a universal, biologically-determined information extraction pattern. Methodology/Principal Findings: Here we monitored the eye movements of Western Caucasian and East Asian observers while they learned, recognized, and categorized by race Western Caucasian and East Asian faces. Western Caucasian observers reproduced a scattered triangular pattern of fixations for faces of both races and across tasks. Contrary to intuition, East Asian observers focused more on the central region of the face. Conclusions/Significance: These results demonstrate that face processing can no longer be considered as arising from a universal series of perceptual events. The strategy employed to extract visual information from faces differs across cultures

A computationally efficient method for hand–eye calibration

Purpose: Surgical robots with cooperative control and semiautonomous features have shown increasing clinical potential, particularly for repetitive tasks under imaging and vision guidance. Effective performance of an autonomous task requires accurate hand–eye calibration so that the transformation between the robot coordinate frame and the camera coordinates is well defined. In practice, due to changes in surgical instruments, online hand–eye calibration must be performed regularly. In order to ensure seamless execution of the surgical procedure without affecting the normal surgical workflow, it is important to derive fast and efficient hand–eye calibration methods. Methods: We present a computationally efficient iterative method for hand–eye calibration. In this method, dual quaternion is introduced to represent the rigid transformation, and a two-step iterative method is proposed to recover the real and dual parts of the dual quaternion simultaneously, and thus the estimation of rotation and translation of the transformation. Results: The proposed method was applied to determine the rigid transformation between the stereo laparoscope and the robot manipulator. Promising experimental and simulation results have shown significant convergence speed improvement to 3 iterations from larger than 30 with regard to standard optimization method, which illustrates the effectiveness and efficiency of the proposed method