Abstract
This chapter analyzes brain mechanisms for launching the attention to video information, describes swarm intelligence to consciously and proactively implement these mechanisms and advances the concepts of “brain-inspired object detection ” and “brain-inspired compressive tracking ,” respectively. Algorithms for swarm intelligence are interpreted as an integration of deep learning with target impulse responses, defining the selected objects in videos for tracking as eigenobjects . Such swarm intelligence achieves the robustness, accuracy and speed simultaneously, as preliminarily validated on challenging data under the unmanned driving scene. Brain mechanisms for a selective cognition to locate eigenobjects and mechanism for the motion tracking are illustrated, taking detection and tracking of dangerous objects as an example. Based on the biological mechanisms, mechanisms for the eigenobjects detection and its motion tracking by brain-inspired robots are analyzed, along with a sketch of the scheme to implement biological mechanisms in integration models. The perspective applications of compressive tracking by brain-inspired robots are preliminarily discussed, and at the end of this chapter, the outline of this book is also presented.
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© 2020 Huazhong University of Science and Technology Press, Wuhan and Springer Nature Singapore Pte Ltd.
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Wang, W., Deng, X., Ding, L., Zhang, L. (2020). Introduction of Brain Cognition. In: Brain-Inspired Intelligence and Visual Perception. Research on Intelligent Manufacturing. Springer, Singapore. https://doi.org/10.1007/978-981-13-3549-5_1
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DOI: https://doi.org/10.1007/978-981-13-3549-5_1
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