Object recognition is a significant approach employed for recognizing suitable objects from the image. Various improvements, particularly in computer vision, are probable to diagnose highly difficult tasks with assistance of local feature detection methodologies. Detecting multi-class quite challenging, and many existing researches have worked enhance overall accuracy. But because certain limit...

Multi object optimization in material selection involves the satisfaction of optimizing multi attributes simultaneously, which analogically corresponds to simultaneous appearance event viewpoint probability theory, thus – becomes assessment “joint probability” these attribute problem. Furthermore, preferential degree candidate is reflected by concept probability, and a quantitative approach for...

Our method studies the complex task of object-centric 3D understanding from a single RGB-D observation. As it is an ill-posed problem, existing methods suffer low performance for both shape and 6D pose size estimation in multi-object scenarios with occlusions. We present ShAPO, joint detection, textured reconstruction, object estimation. Key to ShAPO single-shot pipeline regress shape, appearan...

6D object pose estimation aims to infer the relative between and camera using a single image or multiple images. Most works have focused on predicting without associated uncertainty under occlusion structural ambiguity (symmetricity). However, these demand prior information about shape attributes, this condition is hardly satisfied in reality; even asymmetric objects may be symmetric viewpoint ...

In this paper, an improved genetic algorithm for multi-object optimization is proposed. Simulated annealing is used to local search in genetic algorithms. Furthermore, fuzzy reasoning is adopted to modify crossover probability and mutation probability according to characteristics of population in genetic algorithms instead of fixed parameters. And so, it can be convergence to global optimum qui...

Aiming to address the fast multi-object tracking for dense small object in the cluster background, we review track orientated multi-hypothesis tracking(TOMHT) with consideration of batch optimization. Employing autocorrelation based motion score test and staged hypotheses merging approach, we build our homologous hypothesis generation and management method. A new one-to-many constraint is propo...

In this technical report, we review related works and recent trends in visual vocabulary based web image search, object recognition, mobile visual search, and 3D object retrieval. Especial focuses would be also given for the recent trends in supervised/unsupervised vocabulary optimization, compact descriptor for visual search, as well as in multi-view based 3D object representation.

despite the growing use of evolutionary multi-objective optimization algorithms in different categories of science, these algorithms as a powerful tool in portfolio optimization and specially solving multi-objective portfolio optimization problem is still in its early stages. in this paper, moeas have been used for solving multi-objective portfolio optimization problem in tehran stock market. f...