Active learning for deep visual tracking
Convolutional neural networks (CNNs) have been successfully applied to the single target
tracking task in recent years. Generally, training a deep CNN model requires numerous …
tracking task in recent years. Generally, training a deep CNN model requires numerous …
Integrated sensing and communications for V2I networks: Dynamic predictive beamforming for extended vehicle targets
We investigate sensing-assisted beamforming for vehicle-to-infrastructure (V2I)
communication by exploiting integrated sensing and communications (ISAC) functionalities …
communication by exploiting integrated sensing and communications (ISAC) functionalities …
The LOCATA challenge: Acoustic source localization and tracking
The ability to localize and track acoustic events is a fundamental prerequisite for equip**
machines with the ability to be aware of and engage with humans in their surrounding …
machines with the ability to be aware of and engage with humans in their surrounding …
Immortal tracker: Tracklet never dies
Previous online 3D Multi-Object Tracking (3DMOT) methods terminate a tracklet when it is
not associated with new detections for a few frames. But if an object just goes dark, like …
not associated with new detections for a few frames. But if an object just goes dark, like …
Audio–visual particle flow smc-phd filtering for multi-speaker tracking
Sequential Monte Carlo probability hypothesis density (SMC-PHD) filtering is a popular
method used recently for audio-visual (AV) multi-speaker tracking. However, due to the …
method used recently for audio-visual (AV) multi-speaker tracking. However, due to the …
Occlusion-robust online multi-object visual tracking using a GM-PHD filter with CNN-based re-identification
NL Baisa - Journal of Visual Communication and Image …, 2021 - Elsevier
We propose a novel online multi-object visual tracker using a Gaussian mixture Probability
Hypothesis Density (GM-PHD) filter and deep appearance learning. The GM-PHD filter has …
Hypothesis Density (GM-PHD) filter and deep appearance learning. The GM-PHD filter has …
Variational bayesian inference for audio-visual tracking of multiple speakers
In this article, we address the problem of tracking multiple speakers via the fusion of visual
and auditory information. We propose to exploit the complementary nature and roles of …
and auditory information. We propose to exploit the complementary nature and roles of …
Intensity particle flow smc-phd filter for audio speaker tracking
Non-zero diffusion particle flow Sequential Monte Carlo probability hypothesis density (NPF-
SMC-PHD) filtering has been recently introduced for multi-speaker tracking. However, the …
SMC-PHD) filtering has been recently introduced for multi-speaker tracking. However, the …
Universal learning waveform selection strategies for adaptive target tracking
Online selection of optimal waveforms for target tracking with active sensors has long been a
problem of interest. Many conventional solutions utilize an estimation-theoretic …
problem of interest. Many conventional solutions utilize an estimation-theoretic …
Labelled non-zero particle flow for smc-phd filtering
The sequential Monte Carlo probability hypothesis density (SMC-PHD) filter assisted by
particle flows (PF) has been shown to be promising for audio-visual multi-speaker tracking …
particle flows (PF) has been shown to be promising for audio-visual multi-speaker tracking …