On-device research index

arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

169,051 papers · 148 categories

Trend · papers per month

count % of corpus

6 results for “multi-Bernoulli”

Poisson Multi-Bernoulli Mapping Using Gibbs Samplingstat.ML

This paper solves mapping problems with a novel Gibbs sampling method.

problem Mapping problems with uncertainties in data associations and landmark cardinality.

method Derives a hybrid Poisson, multi-Bernoulli mixture distribution using a conjugate prior and Poisson process prior. Uses Gibbs sampling to sample from the posterior.

result The proposed method outperforms state-of-the-art methods on synthetic data.

mapping Gibbs sampling multi-Bernoulli Poisson process landmarks

2018-11-07abs ↗pdf ↗

Trajectory Poisson multi-Bernoulli mixture filter for traffic monitoring using a dronecs.CV

A drone-based MOT algorithm tracks vehicles using neural network detections and TPMBM filter.

problem Tracking multiple vehicles from drone-mounted cameras.

method Neural network for object detection, TPMBM filter for trajectory estimation, von-Mises Fisher distribution for DOA.

result TPMBM filter optimally estimates vehicle trajectories.

drone traffic monitoring multi-object tracking TPMBM filter neural network

2023-06-29abs ↗pdf ↗

Linear Complexity Gibbs Sampling for Generalized Labeled Multi-Bernoulli Filteringstat.ML

New Gibbs sampling reduces GLMB filtering complexity to linear time.

problem NP-hard GLMB density computation in multi-object systems.

method Tempered Gibbs sampler exploiting GLMB structure.

result Linear complexity

\mathcal{O}(T(P+M))

for GLMB filtering.

Gibbs sampling GLMB filtering NP-hard multi-object systems linear complexity

2022-11-29abs ↗pdf ↗

Multi-Base Station Cooperative Sensing with AI-Aided Trackingeess.SP

Joint sensing and communication network improves target localization and reduces communication load.

problem Efficiently localize multiple targets with reduced communication overhead.

method Multi-base station cooperative sensing with AI-aided clustering and tracking.

result Optimal sub-pattern assignment (OSPA) error less than 60 cm with reduced communication capacity.

cooperative sensing multi-base station AI-aided tracking convolutional neural network multi-Bernoulli mixture filter

2023-10-31abs ↗pdf ↗

Bayesian nonparametric modeling for predicting dynamic dependencies in multiple object trackingcs.LG

Bayesian methods improve tracking multiple objects through dynamic dependencies.

problem Tracking multiple objects with time-varying cardinality and unordered measurements.

method Employing Bayesian nonparametric models, specifically dependent Dirichlet and Pitman-Yor processes, for state estimation and Monte Carlo sampling for trajectory learning.

result The proposed methods outperform existing algorithms in estimating the time-varying number of objects and identifying object associations.

Bayesian nonparametrics multiple object tracking dynamic dependencies Monte Carlo sampling Bayesian filters

2020-04-22abs ↗pdf ↗

Inference for multiple object tracking: A Bayesian nonparametric approachcs.LG

Bayesian nonparametric models improve multi-object tracking robustness and flexibility.

problem Challenges in multi-object tracking, including time-dependent cardinality, unordered measurements, and object labeling.

method Robust nonparametric methods for state prior modeling, incorporating dynamic object birth/death and survival.

result Proposed models estimate time-dependent object cardinality, provide object labeling, and identify associated measurements.

multi-object tracking Bayesian nonparametric robustness dynamic modeling object labeling

2019-09-16abs ↗pdf ↗