AIMC Topic: Motion Perception

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Depth Perception Based on the Interaction of Binocular Disparity and Motion Parallax Cues in Three-Dimensional Space.

Sensors (Basel, Switzerland)
BACKGROUND AND OBJECTIVES: Depth perception of the human visual system in three-dimensional (3D) space plays an important role in human-computer interaction and artificial intelligence (AI) areas. It mainly employs binocular disparity and motion para...

Pre-training artificial neural networks with spontaneous retinal activity improves motion prediction in natural scenes.

PLoS computational biology
The ability to process visual stimuli rich with motion represents an essential skill for animal survival and is largely already present at the onset of vision. Although the exact mechanisms underlying its maturation remain elusive, spontaneous activi...

TSOM: Small object motion detection neural network inspired by avian visual circuit.

Neural networks : the official journal of the International Neural Network Society
Detecting small moving objects in complex backgrounds from an overhead perspective is a highly challenging task for machine vision systems. As an inspiration from nature, the avian visual system is capable of processing motion information in various ...

Learning to segment self-generated from externally caused optic flow through sensorimotor mismatch circuits.

Neural networks : the official journal of the International Neural Network Society
Efficient sensory detection requires the capacity to ignore task-irrelevant information, for example when optic flow patterns created by egomotion need to be disentangled from object perception. To investigate how this is achieved in the visual syste...

A computationally efficient and robust looming perception model based on dynamic neural field.

Neural networks : the official journal of the International Neural Network Society
There are primarily two classes of bio-inspired looming perception visual systems. The first class employs hierarchical neural networks inspired by well-acknowledged anatomical pathways responsible for looming perception, and the second maps nonlinea...

Perception of motion salience shapes the emergence of collective motions.

Nature communications
Despite the profound implications of self-organization in animal groups for collective behaviors, understanding the fundamental principles and applying them to swarm robotics remains incomplete. Here we propose a heuristic measure of perception of mo...

Position-Aware Participation-Contributed Temporal Dynamic Model for Group Activity Recognition.

IEEE transactions on neural networks and learning systems
Group activity recognition (GAR) aiming at understanding the behavior of a group of people in a video clip has received increasing attention recently. Nevertheless, most of the existing solutions ignore that not all the persons contribute to the grou...

Estimating heading from optic flow: Comparing deep learning network and human performance.

Neural networks : the official journal of the International Neural Network Society
Convolutional neural networks (CNNs) have made significant advances over the past decade with visual recognition, matching or exceeding human performance on certain tasks. Visual recognition is subserved by the ventral stream of the visual system, wh...

Predictive Visual Motion Extrapolation Emerges Spontaneously and without Supervision at Each Layer of a Hierarchical Neural Network with Spike-Timing-Dependent Plasticity.

The Journal of neuroscience : the official journal of the Society for Neuroscience
The fact that the transmission and processing of visual information in the brain takes time presents a problem for the accurate real-time localization of a moving object. One way this problem might be solved is extrapolation: using an object's past t...

A bioinspired angular velocity decoding neural network model for visually guided flights.

Neural networks : the official journal of the International Neural Network Society
Efficient and robust motion perception systems are important pre-requisites for achieving visually guided flights in future micro air vehicles. As a source of inspiration, the visual neural networks of flying insects such as honeybee and Drosophila p...