首页|University of Carlos Ⅲ Researcher Details Research in Robotics (Integrating Egocentric and Robotic Vision for Object Identification Using Siamese Networks and Superquadric Estimations in Partial Occlusion Scenarios)
University of Carlos Ⅲ Researcher Details Research in Robotics (Integrating Egocentric and Robotic Vision for Object Identification Using Siamese Networks and Superquadric Estimations in Partial Occlusion Scenarios)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
Mdpi
Fresh data on robotics are presented in a new report. According to news reporting out of Madrid, Spain, by NewsRx editors, research stated, "This paper introduces a novel method that enables robots to identify objects based on user gaze, tracked via eye-tracking glasses." Financial supporters for this research include Companion-cm, Inteligencia Artificial Y Modelos Cogni- tivos Para La Interaccion Simetrica Humano-robot En El Ambito De La Robotica Asistencial; Proyectos Sinergicos De I+D La Comunidad De Madrid. Our news correspondents obtained a quote from the research from University of Carlos III: "This is achieved without prior knowledge of the objects' categories or their locations and without external markers. The method integrates a two-part system: a category-agnostic object shape and pose estimator using superquadrics and Siamese networks. The superquadrics-based component estimates the shapes and poses of all objects, while the Siamese network matches the object targeted by the user's gaze with the robot's viewpoint. Both components are effectively designed to function in scenarios with partial occlusions. A key feature of the system is the user's ability to move freely around the scenario, allowing dynamic object selection via gaze from any position. The system is capable of handling significant viewpoint differences between the user and the robot and adapts easily to new objects."
University of Carlos ⅢMadridSpainEuropeEmerging TechnologiesMachine LearningRoboticsRobots
NETL
NSTL
Mdpi
