Create Machine Vision Inspired by Eagle Eye

Duan, Haibin; Xu, Xiaojun

doi:10.34133/2022/9891728

Cited by 8 publications

(5 citation statements)

References 37 publications

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“…These networks transcribe real-time sensory data into a universal language of tokens, which are then fed into the encoder for further nuanced interpretation. Furthermore, we recognize the importance of personal background variables including age, social role, and gender in adjusting emotional response and driving behavior [ 60 – 64 ]. Our model makes allowances for these factors to ensure that our emotional regulation framework is not only reactive but also predictive and personalized.…”

Section: Big Models and Edge Computing Inside Vehiclesmentioning

confidence: 99%

Parallel Driving with Big Models and Foundation Intelligence in Cyber–Physical–Social Spaces

Wang,

Huang,

Tian

et al. 2024

Research

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Recent years have witnessed numerous technical breakthroughs in connected and autonomous vehicles (CAVs). On the one hand, these breakthroughs have significantly advanced the development of intelligent transportation systems (ITSs); on the other hand, these new traffic participants introduce more complex and uncertain elements to ITSs from the social space. Digital twins (DTs) provide real-time, data-driven, precise modeling for constructing the digital mapping of physical-world ITSs. Meanwhile, the metaverse integrates emerging technologies such as virtual reality/mixed reality, artificial intelligence, and DTs to model and explore how to realize improved sustainability, increased efficiency, and enhanced safety. More recently, as a leading effort toward general artificial intelligence, the concept of foundation model was proposed and has achieved significant success, showing great potential to lay the cornerstone for diverse artificial intelligence applications across different domains. In this article, we explore the big models embodied foundation intelligence for parallel driving in cyber-physical-social spaces, which integrate metaverse and DTs to construct a parallel training space for CAVs, and present a comprehensive elucidation of the crucial characteristics and operational mechanisms. Beyond providing the infrastructure and foundation intelligence of big models for parallel driving, this article also discusses future trends and potential research directions, and the “6S” goals of parallel driving.

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Section: Big Models and Edge Computing Inside Vehiclesmentioning

confidence: 99%

Parallel Driving with Big Models and Foundation Intelligence in Cyber–Physical–Social Spaces

Wang,

Huang,

Tian

et al. 2024

Research

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“…The eagle has the sharpest visual acuity among all animals, whose powerful vision perception mechanisms bring abundant inspiration for traditional visual applications. Biological eagle eye vision technology provides a creative way to solve visual perception issues [ 120 ]. Therein, the theoretical method and application technology of bionic visual perception could promote the development of environment perception and recognition technology.…”

Section: Future Prospectsmentioning

confidence: 99%

From animal collective behaviors to swarm robotic cooperation

Duan

Huo

Fan

2023

National Science Review

Self Cite

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The collective behaviors of animals, from schooling fish to packing wolves and flocking birds, display plenty of fascinating phenomena that result from simple interaction rules among individuals. The emergent intelligent properties of the animal collective behaviors, such as self-organization, robustness, adaptability, and expansibility, have inspired the design of autonomous unmanned swarm systems. This article reviews several typical natural collective behaviors, introduces the origin and connotation of swarm intelligence, gives the application case of animal collective behaviors. On this basis, the article focuses on the forefront of progress and bionic achievements of aerial, ground and marine robotics swarms, illustrating the mapping relationship from biological cooperative mechanisms to cooperative unmanned cluster systems. Finally, considering the significance of Coexisting-Cooperative-Cognitive (Tri-Co) human-machine system, the key technologies to be solved are given as the reference directions for the subsequent exploration.

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“…Most bionic systems took the bionic idea to guide the design in mechanical-inspired way [7][8][9] and functional-inspired way [10][11][12][13][14][15]. As for biomimetic visual system, Duan et al [10] designed the bionic perception system for aircraft refuelling target detection, and the attention mechanism of raptors' eye was the key point for accurate detection.…”

Section: Biomimetic Visual Systemmentioning

confidence: 99%

“…Most bionic systems took the bionic idea to guide the design in mechanical‐inspired way [7–9] and functional‐inspired way [10–15]. As for biomimetic visual system, Duan et al.…”

Section: Related Workmentioning

confidence: 99%

Hawk‐eye‐inspired perception algorithm of stereo vision for obtaining orchard 3D point cloud navigation map

Zhang

Chen

et al. 2022

CAAI Trans on Intel Tech

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The binocular stereo vision is the lowest cost sensor for obtaining 3D information. Considering the weakness of long-distance measurement and stability, the improvement of accuracy and stability of stereo vision is urgently required for application of precision agriculture. To address the challenges of stereo vision long-distance measurement and stable perception without hardware upgrade, inspired by hawk eyes, higher resolution perception and the adaptive HDR (High Dynamic Range) were introduced in this paper. Simulating the function from physiological structure of 'deep fovea' and 'shallow fovea' of hawk eye, the higher resolution reconstruction method in this paper was aimed at accuracy improving. Inspired by adjustment of pupils, the adaptive HDR method was proposed for high dynamic range optimisation and stable perception. In various light conditions, compared with default stereo vision, the accuracy of proposed algorithm was improved by 28.0% evaluated by error ratio, and the stability was improved by 26.56% by disparity accuracy. For fixed distance measurement, the maximum improvement was 78.6% by standard deviation. Based on the hawk-eye-inspired perception algorithm, the point cloud of orchard was improved both in quality and quantity. The hawk-eye-inspired perception algorithm contributed great advance in binocular 3D point cloud reconstruction in orchard navigation map. K E Y W O R D S adaptive high dynamic range, binocular stereo vision, hawk-eye-inspired perception, point cloud of orchard, super-resolution generative adversarial network 1 | INTRODUCTION Precision agriculture needs accurate perception. In orchard automation agricultural production, accurate and stable 3D navigation map is the basis of UAV and unmanned vehicle operation [1]. Agricultural production is very sensitive to the cost. Binocular stereo vision has advantages over other sensors because of low cost, high sampling frequency, large amount of data obtaining ability, low-power consumption, and light weight, which is widely used in the all-production links in smart agriculture [2, 3]. However, in most condition of agricultural outdoor working environment, optical sensors and This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Create Machine Vision Inspired by Eagle Eye

Cited by 8 publications

References 37 publications

Parallel Driving with Big Models and Foundation Intelligence in Cyber–Physical–Social Spaces

Parallel Driving with Big Models and Foundation Intelligence in Cyber–Physical–Social Spaces

From animal collective behaviors to swarm robotic cooperation

Hawk‐eye‐inspired perception algorithm of stereo vision for obtaining orchard 3D point cloud navigation map

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