Properties of neuronal facilitation that improve target tracking in natural pursuit simulations

Abstract

Although flying insects have limited visual acuity (approx. 18) and relatively small brains, many species pursue tiny targets against cluttered backgrounds with high success. Our previous computational model, inspired by electrophysiological recordings from insect 'small target motion detector' (STMD) neurons, did not account for several key properties described from the biological system. These include the recent observations of response 'facilitation' (a slow build-up of response to targets that move on long, continuous trajectories) and 'selective attention', a competitive mechanism that selects one target from alternatives. Here, we present an elaborated STMD-inspired model, implemented in a closed loop target-tracking system that uses an active saccadic gaze fixation strategy inspired by insect pursuit. We test this system against heavily cluttered natural scenes. Inclusion of facilitation not only substantially improves success for even short-duration pursuits, but it also enhances the ability to 'attend' to one target in the presence of distracters. Our model predicts optimal facilitation parameters that are static in space and dynamic in time, changing with respect to the amount of background clutter and the intended purpose of the pursuit. Our results provide insights into insect neurophysiology and show the potential of this algorithm for implementation in artificial visual systems and robotic applications.

Properties of predictive gain modulation in a dragonfly visual neuron

“…Currently, the neuronal circuits responsible for modulating this neuronal sensitivity and gain magnitude are unknown. Target tracking and pursuit simulations that implemented a dragonfly-inspired predictive gain modulation mechanism found that the optimal facilitation time constant should be variable, depending on the spatial statistics of a scene (Bagheri et al, 2015). In cluttered scenes, a longer time constant increases performance because of the high likelihood of temporary target occlusions; however, in more sparse scenery, a rapid facilitation time course is beneficial, as the target remains highly discriminable.…”

Towards Computational Models and Applications of Insect Visual Systems for Motion Perception: A Review

“…More specifically, the ESTMD-EMD indicates that the ESTMD cascades with the EMD while the EMD-ESTMD indicates that the EMD cascades with the ESTMD. These two hybrid models have been successfully used for target tracking against cluttered backgrounds in an autonomous mobile ground robot [9,11,10]. Another directionally selective STMD model, the directionally selective small target motion detector (DSTMD in the Fig.…”

Performance of an insect-inspired target tracker in natural conditions

“…This cumulative error usually arises from uncertainty in object location or target occlusion, with drift resulting in tracking failure. State-of-the-art trackers use techniques such as robust loss functions (Leistner et al, 2009; Masnadi-Shirazi et al, speed of pursued prey (Bagheri et al, 2015).…”