KEYWORDS: Statistical analysis, Detection and tracking algorithms, Data modeling, Databases, Feature extraction, Monte Carlo methods, Object recognition, Statistical modeling, Model-based design, Process modeling
In order to gain generality, robustness and efficiency in search, a novel search is proposed based on a representation called `Depth aspect image' is proposed as a controllable two-dimensional representation of local depth distribution used in cooperation with a distinct `Voxel framing', which enables effective reference coordination without any prominent features, such as vertices or edges. A robust statistical estimator called `Least quantile of residuals' is furthermore introduced for robust matching, which can be utilized for both depth matching and model verification.
Since the proposed method is of model-based approach with possible views of local structures, the computation cost for matching has to be reduced by introducing random sampling and an effective hashing.
Experiments with real scenes show the effectiveness of the proposed method.