7-point Method Research Articles

Evaluation of the feasibility of using skin temperature to predict overall thermal sensation in non-uniform thermal environments

Skin temperature is an important physiological parameter that reflects human thermal sensation. However, it is uncertain whether it can evaluate overall thermal sensation in non-uniform thermal environments. This study aims to explore the feasibility of using skin temperature to predict overall thermal sensation in non-uniform environments. The overall thermal sensation votes and skin temperatures were obtained in a non-uniform thermal environment with local cooling on the chest in a climate chamber. The predictive power of the representative skin temperature (RST) estimated from five different methods was examined by analysing its sensitivity and the correlation between the overall thermal sensation and the RST. The RSTs estimated from the 7-point method with the measurement site of trunk assigned on the chest and the 1-point method with a measurement site at the centre of the chest had high sensitivity and coefficients of determination. They could reflect overall thermal sensation in the non-uniform environments with local cooling on the chest. The results imply that skin temperature could be used to evaluate overall thermal sensation in non-uniform environments. The overall thermal sensation in non-uniform environments can be evaluated by the RST if, when determining the RST, the measuring site exposed to local cooling is involved and given a high weight.

An efficient solution to the five-point relative pose problem

An efficient algorithmic solution to the classical five-point relative pose problem is presented. The problem is to find the possible solutions for relative camera pose between two calibrated views given five corresponding points. The algorithm consists of computing the coefficients of a tenth degree polynomial in closed form and, subsequently, finding its roots. It is the first algorithm well-suited for numerical implementation that also corresponds to the inherent complexity of the problem. We investigate the numerical precision of the algorithm. We also study its performance under noise in minimal as well as overdetermined cases. The performance is compared to that of the well-known 8 and 7-point methods and a 6-point scheme. The algorithm is used in a robust hypothesize-and-test framework to estimate structure and motion in real-time with low delay. The real-time system uses solely visual input and has been demonstrated at major conferences.