Explore optical flow, a key computer vision field for motion detection and scene dynamics. Learn about classic and deep learning techniques today!
PMW3901 is an optical flow ASIC that computes the flow internally and provides a difference in pixels between each frame. It uses a tracking sensor that is similar to what you would find in a computer
Most algorithms for steering, obstacle avoidance, and moving object detection rely on accurate self-motion estimation, a problem animals solve in real
The ARK Flow Open Source Optical Flow and Distance Sensor is an open source optical flow sensor including a Broadcom AFBR lidar which uses the CAN
Our model advances a biologically plausible solution by extending predictive coding models with the ability to distinguish self-generated from externally caused optic flow. We first show
Optical flow or optic flow is the pattern of apparent motion of objects, surfaces, and edges in a visual scene caused by the relative motion between an observer and a scene. Optical flow can also
Exploring the capabilities of optical flow sensors by transforming a old optical mouse into a handheld motion tracking device.
Notably, the state-of-the-art performance achieved by VideoFLows (Shi et al., 2023) is attributed to its utilization of a TRi-frame Optical Flow module (TROF), a technique that jointly
Discover optical flow sensors for precise drone positioning. Learn how these vision-based systems enable stable hovering and indoor navigation.
This article describes how to setup the PX4FLOW (Optical Flow) Sensor which can be used for Non-GPS navigation. The PX4FLOW is not yet supported in Plane or
We construct a joint inter-frame-supervised depth and optical flow estimation framework, which predicts depths in different motions by minimizing pixel wrap errors between the photometric re
To address this, some learning-based optical flow approaches use self-supervised learning (sometimes called unsupervised learning) to reduce the need for large datasets with ground-truth data and
We present a self-supervised learning approach for op-tical flow. Our method distills reliable flow estimations from non-occluded pixels, and uses these predictions as ground truth to learn optical flow
FlowDiffuser estimates optical flow through a ''noise-to-flow'' strategy, progressively eliminating noise from ran-domly generated flows conditioned on the provided pairs. To optimize accuracy and
Our model advanced a novel, biologically plausible solution to this question, which extends predictive coding models with the ability to distinguish
A local flow fusion module is designed to smooth the optical flow, taking into account the prior knowledge of the blurred effect of gel deformation. We trained the proposed self-supervised
Learn how to make your own indoor optical flow drone, capable of indoor position locks without GPS. You won''t believe how easy it is.
Therefore, we propose FlowDepth, where a Dynamic Motion Flow Module (DMFM) decouples the optical flow by a mechanism-based approach and warps the dynamic regions thus solving the mismatch
A prototype fiber-optic flow sensor system was developed and tested both in the lab and in the field; the test results have demonstrated that this fiber optic flow sensor system can detect flow rates of fluids
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In addition, two attention modules are embedded into each pyramidal level, which can refine features at different scale. We evaluate our method on MPI-Sintel and KITTI. The experimental results show that
This paper introduces two synergistic techniques, Self-Cleaning Iteration (SCI) and Regression Focal Loss (RFL), designed to enhance the capabilities of optical flow mod-els, with a focus on addressing
Optical flow estimation is crucial to a variety of vision tasks. Despite substantial recent advancements, achieving real-time on-device optical flow estimation remains a complex challenge.
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