On Real-Time Synthetic Primate Vision

The primate vision system exhibits numerous capabilities. Some important basic visual competencies include: 1) a consistent representation of visual space across eye movements; 2) egocentric spatial perception; 3) coordinated stereo fixation upon and pursuit of dynamic objects; and 4) attentional gaze deployment. We present a synthetic vision system that incorporates these competencies.We hypothesize that similarities between the underlying synthetic system model and that of the primate vision system elicit accordingly similar gaze behaviors. Psychophysical trials were conducted to record human gaze behavior when free-viewing a reproducible, dynamic, 3D scene. Identical trials were conducted with the synthetic system. A statistical comparison of synthetic and human gaze behavior has shown that the two are remarkably similar

Intelligent Vehicles

International audience; This chapter describes the emerging robotics application field of intelligent vehicles motor vehicles that have autonomous functions and capabilities. The chapter is organized as follows:- Section 62.1 provides a motivation for why the development of intelligent vehicles is important, a brief history of the field, and the potential benefits of the technology.- Section 62.2 describes the technologies that enable intelligent vehicles to sense vehicle, environment, and driver state, work with digital maps and satellite navigation, and communicate with intelligent transportation infrastructure.- Section 62.3 describes the challenges and solutions associated with road scene understanding a key capability for all intelligent vehicles.- Section 62.4 describes advanced driver assistance systems, which use the robotics and sensing technologies described earlier to create new safety and convenience systems for motor vehicles, such as collision avoidance, lane keeping, and parking assistance.- Section 62.5 describes driver monitoring technologies that are being developed to mitigate driver fatigue, inattention, and impairment.- Section 62.6 describes fully autonomous intelligent vehicles systems that have been developed and deployed.- Sections 62.7 and 62.8 conclude the chapter with a discussion of future prospects, and provide references to further reading and additional resources. Document type: Part of book or chapter of boo

Common Sense Recommendations for the Application of Tax Law to Digital Assets

In response to the Joint Committee on Taxation’s July 2023 request for comments on application of various Internal Revenue Code sections on digital assets, we propose a consistent set of rules to apply current law to digital assets. We highlight that the underlying economics and characteristics of transactions should be the primary concern for the application of rules and the valuation of digital assets. We believe any digital asset rules should (1) treat classes of digital assets with unique characteristics differently based on their economics, (2) minimize incentives for users to engage in tax-motivated structuring of transactions, and (3) allow the Internal Revenue Service authority to react to and regulate new classes of digital assets as they are created. We do not believe that the unique features of digital assets are a challenge to applying current law or warrant special tax preferred treatment

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The difficulty associated with programing existing robots is one of the main impediments to them finding application in domestic environments such as the home. A promising method for simplifying robot programing is Programing by Demonstration (PbD). Here, an end user can provide a demonstration of the task to be programed, with a PbD “interface ” interpreting the demonstration in order to determine low-level control details for the robot. A key aspect of the interpretation process is to make it robust to the noise typically included in a demonstration by the human. In this paper we present a method to help identify and eliminate any noise present in the demonstration. Our method involves two steps. The first step uses the demonstration to build up a partial knowledge of the geometry present in the task. Statistical regression analysis is used on demonstrated trajectories to determine equations describing curved surfaces in configuratio

Programing by Demonstration: Coping with Suboptimal Teaching Actions

The difficulty associated with programing existing robots is one of the main impediments to them finding application in domestic environments such as the home. A promising method for simplifying robot programing is Programing by Demonstration (PbD). Here, an end user can provide a demonstration of the task to be programed, with a PbD "interface" interpreting the demonstration in order to determine low-level control details for the robot. A key aspect of the interpretation process is to make it robust to the noise typically included in a demonstration by the human. In this paper we present a method to help identify and eliminate any noise present in the demonstration. Our method involves two steps. The first step uses the demonstration to build up a partial knowledge of the geometry present in the task. Statistical regression analysis is used on demonstrated trajectories to determine equations describing curved surfaces in configuration space. The second step in our method uses the geometric information obtained in the first step to determine if there are more optimal paths than those demonstrated for completing the task. If there are, our method proposes these as the appropriate control commands for the robot. We show the validity of our approach by presenting successful experiments on a realistic household-type task---changing rolls on a paper roll holder

A Real-World Vision System: Mechanism, Control and Vision Processing

This paper reports on the development of a multi-purpose active visual sensor system for real-world application. The Cable-Drive Active-Vision Robot (CeDAR) has been designed for use on a diverse range of platforms, to perform a diverse range of tasks. T

Fast Radial Symmetry for Detecting Points of Interest

A new transform is presented that utilizes local radial symmetry to highlight points of interest within a scene. Its low-computational complexity and fast runtimes makes this method well-suited for real-time vision applications. The performance of the transform is demonstrated on a wide variety of images and compared with leading techniques from the literature. Both as a facial feature detector and as a generic region of interest detector the new transform is seen to offer equal or superior performance to contemporary techniques at a relatively low-computational cost. A real-time Implementation of the transform is presented running at over 60 frames per second on a standard Pentium III PC