Conditional-mean estimation via jump-diffusion processes in multiple target tracking/recognition
Explore this paper's citation graph
Summary
A new algorithm is presented for generating the conditional mean estimates of functions of target positions, orientations and type in recognition, and tracking of an unknown number of targets and target types using a Bayesian approach.
- Type
- article
- Published
- 1995-11-01
- Cited by
- 138
- References
- 28
- OpenAlex
- https://openalex.org/W2047339782
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:2160966
Keywords
Computer science, Tracking (education), Jump, Algorithm, Artificial intelligence
References
- Spatial Statistics and Bayesian Computation
- Computer-generated image algebras
- A signal subspace approach to multiple emitter location and spectral estimation
- REPRESENTATIONS OF KNOWLEDGE IN COMPLEX SYSTEMS
- Introduction to the theory of random processes
- Stochastic Complexity and Modeling
- Tracking in a cluttered environment with probabilistic data association
- Advances in Pattern Theory
- Maximum-likelihood narrow-band direction finding and the EM algorithm
- A UNIVERSAL PRIOR FOR INTEGERS AND ESTIMATION BY MINIMUM DESCRIPTION LENGTH
- Control systems design: An introduction to state-space methods : Bernard Friedland
- Multiple target direction of arrival tracking
- A method of sieves for multiresolution spectrum estimation and radar imaging
- Multiple target angle tracking using sensor array outputs
- Tracking the direction of arrival of multiple moving targets
- An efficient algorithm for tracking the angles of arrival of moving targets
- The use of maximum likelihood estimation for forming images of diffuse radar targets from delay-Doppler data
- Tracking and data association
- Statistics of Directional Data
- Statistics of Directional Data
Cited by
- Sensor Management Using Relevance Feedback Learning
- Recognition performance from synthetic aperture radar imagery subject to system resource constraints
- Discrimination and identification of unexploded ordinances (UXO) using airborne magnetic gradients
- Multitarget Tracking Using a Particle Filter Representation of the Joint Multitarget Density
- An efficient Bayesian algorithm for joint target tracking and classification
- A nonlinear filter for real-time joint tracking and recognition
- A kernel particle filter algorithm for joint tracking and classification
- A Particle Filtering Approach to Joint Passive Radar Tracking and Target Classification
- Reversible jump Markov chain Monte Carlo
- Towards Fully Automatic Optimal Shape Modeling
- Non-cooperative target classification and tracking
- A compact probability model for natural clutter
- Multiple target tracking with a pixelized sensor
- A microdensity approach to multitarget tracking
- A nonlinear filtering method for geometric subspace tracking
- Target detection and recognition using Markov modeling and probability updating
- Marked point process in image analysis
- Deformable template models: A review
- Efficient estimation of thermodynamic state incorporating Bayesian model order selection
- Adaptive data fusion using finite-set statistics
Related papers
- American Put-call Symmtry in Jump Diffusion Model
- Accuracy of 3D motion tracking using a stereocamera
- Perpetual American Put with Spectrally Negative Jump - Uniform & Binomial Jump Diffusion Processes
- STUDYING THE CO-MOVEMENTS OF STOCK MARKETS BASED ON A TWO-DIMENSION JUMP DIFFUSION MODEL
- Numerical Solution of Jump-Diffusion SDEs
- Deriving appropriate boundary conditions, and accelerating position-jump simulations, of diffusion using non-local jumping