The research on multi-object tracking (MOT) is essentially to solve for the data association assignment, the core of which is to design the association cost as discriminative as possible. Generally speaking, the match ambiguities caused by similar appearances of objects and the moving cameras make the data association perplexing and challenging. In this paper, we propose a new heuristic method ...

Neural networks have been used to carryout calibration process in fringe projection profilometry for the measurement of three-dimensional object shape. The calibration procedure uses several calibration planes whose positions in space are known. Radial basis function based networks and multi-layer perceptron networks are investigated for the phase recovery. Preliminary studies are also presente...

In this short survey of the applications of wide-field, multi-object spectroscopy to galaxy evolution, large-scale structure and cosmology, I interleave summaries of the general goals and state of play in these fields with specific examples based on my own recent work. I first briefly review the goals and figures of merit for current and future redshift surveys, before examining some recent res...

In this short survey of the applications of wide-field, multi-object spectroscopy to galaxy evolution, large-scale structure and cosmology, I interleave summaries of the general goals and state of play in these fields with specific examples based on my own recent work. I first briefly review the goals and figures of merit for current and future redshift surveys, before examining some recent res...

The area-to-point kriging method (ATPK) is an important technology of downscaling without auxiliary information in remote sensing. However, it uses a constant semivariogram to downscale geospatial variables, which ignores the spatial heterogeneity between objects. To deal with this kind heterogeneity, study proposes fuzzy object-based ATPK method, mainly consists three steps: extraction objects...

Extracting and tracking active objects are two major issues in surveillance and monitoring applications such as nuclear reactors, mine security, and traffic controllers. In this paper, a block-based similarity algorithm is proposed in order to detect and track objects in the successive frames. We define similarity and cost functions based on the features of the blocks, leading to less computati...

In F-logic and RIF, objects (frames) are de ned entirely separately from function and predicate applications. In POSL and RuleML, these fundamental notions are integrated by permitting applications with optional object identi ers and, orthogonally, arguments that are positional or slotted. The resulting positional-slotted, object-applicative (psoa) terms are given a novel formalization, reducin...

This paper presents a Bayesian framework for multi-cue 3D object tracking of deformable objects. The proposed spatio-temporal object representation involves a set of distinct linear subspace models or Dynamic Point Distribution Models (DPDMs), which can deal with both continuous and discontinuous appearance changes; the representation is learned fully automatically from training data. The repre...