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[IEEE 2018 24th International Conference on Pattern Recognition (ICPR) - Beijing (2018.8.20-2018.8.24)] 2018 24th International Conference on Pattern Recognition (ICPR) - Visual Tracking with Breeding Fireflies using Brightness from Background-Foreground Information
摘要： Visual target tracking involves object localization in image sequences. This is achieved by optimizing image feature similarity based objective functions in object state space. Meta-heuristic algorithms have shown promising results in solving hard optimization problems where gradients are not available. This motivated us to use Firefly algorithms in visual object tracking. The object state is represented by its bounding box parameters and the target is modeled by its color distribution. This work has two significant contributions. First, we propose a hybrid firefly algorithm where genetic operations are performed using Real-coded Genetic Algorithm (RGA). Here, the crossover operation is modified by incorporating parent velocity information. Second, the firefly brightness is computed from both foreground and background information (as opposed to only foreground). This helps in handling scale implosion and explosion problems. The proposed approach is benchmarked on challenging sequences from VOT2014 dataset and is compared against other baseline trackers and metaheuristic algorithms.
关键词： Genetic algorithm,Foreground-background information,Optimization,Visual tracking,Firefly algorithm,Object localization
更新于2025-09-19 17:15:36
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An open-source high-speed infrared videography database to study the principles of active sensing in freely navigating rodents
摘要： Background: Active sensing is crucial for navigation. It is characterized by self-generated motor action controlling the accessibility and processing of sensory information. In rodents, active sensing is commonly studied in the whisker system. As rats and mice modulate their whisking contextually, they employ frequency and amplitude modulation. Understanding the development, mechanisms, and plasticity of adaptive motor control will require precise behavioral measurements of whisker position. Findings: Advances in high-speed videography and analytical methods now permit collection and systematic analysis of large datasets. Here, we provide 6,642 videos as freely moving juvenile (third to fourth postnatal week) and adult rodents explore a stationary object on the gap-crossing task. The dataset includes sensory exploration with single- or multi-whiskers in wild-type animals, serotonin transporter knockout rats, rats received pharmacological intervention targeting serotonergic signaling. The dataset includes varying background illumination conditions and signal-to-noise ratios (SNRs), ranging from homogenous/high contrast to non-homogenous/low contrast. A subset of videos has been whisker and nose tracked and are provided as reference for image processing algorithms. Conclusions: The recorded behavioral data can be directly used to study development of sensorimotor computation, top-down mechanisms that control sensory navigation and whisker position, and cross-species comparison of active sensing. It could also help to address contextual modulation of active sensing during touch-induced whisking in head-fixed vs freely behaving animals. Finally, it provides the necessary data for machine learning approaches for automated analysis of sensory and motion parameters across a wide variety of signal-to-noise ratios with accompanying human observer-determined ground-truth.
关键词： sensorimotor computation,goal-directed behavior,object localization,whisking,mouse,rat,mystacial vibrissae
更新于2025-09-19 17:15:36