Visual motion processing and human tracking behavior
원문 초록
The accurate visual tracking of a moving object is a human fundamental skill that allows to reduce the relative slip and instability of the object's image on the retina, thus granting a stable, high-quality vision. In order to optimize tracking performance across time, a quick estimate of the object's global motion properties needs to be fed to the oculomotor system and dynamically updated. Concurrently, performance can be greatly improved in terms of latency and accuracy by taking into account predictive cues, especially under variable conditions of visibility and in presence of ambiguous retinal information. Here, we review several recent studies focusing on the integration of retinal and extra-retinal information for the control of human smooth pursuit.By dynamically probing the tracking performance with well established paradigms in the visual perception and oculomotor literature we provide the basis to test theoretical hypotheses within the framework of dynamic probabilistic inference. We will in particular present the applications of these results in light of state-of-the-art computer vision algorithms.
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R1-Track: Direct Application of MLLMs to Visual Object Tracking via Reinforcement Learning
Exploiting Lightweight Hierarchical ViT and Dynamic Framework for Efficient Visual Tracking
Towards Effective and Efficient Adversarial Defense with Diffusion Models for Robust Visual Tracking
CLDTracker: A Comprehensive Language Description for Visual Tracking
Efficient Motion Prompt Learning for Robust Visual Tracking
Towards Adaptive Meta-Gradient Adversarial Examples for Visual Tracking
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