This paper presents a new method for the relaxation of multiview registration error. The multiview registration problem is represented using a graph. Each node and each edge in the graph represents a 3-D data set and a pairwise registration, respectively. Assuming that all the pairwise registration processes have converged to fine results, this paper shows that the multiview registration problem can be converted into a quadratic programming problem of Lie algebra parameters. The constraints are obtained from every cycle of the graph to eliminate the accumulation errors of global registration. A linear solution is proposed to distribute the accumulation error to proper positions in the graph, as specified by the quadratic model. Since the proposed method does not involve the original 3-D data, it has low time and space complexity. Additionally, the proposed method can be embedded into a trust-region algorithm and, thus, can correctly handle the nonlinear effects of large accumulation errors, while preserving the global convergence property to the first-order critical point. Experimental results confirm both the efficiency and the accuracy of the proposed method.
This paper shows that, by simply adding a triangle aperture (TA) in front of a camera lens, iris autofocus can be easily achieved. Through the TA, the corneal reflection of a light source forms a triangle glint on the image plane. The size and orientation of the glint can be used to infer the amount and the direction of the focus adjustment. A gradient-descent autofocus control law is proposed for uncalibrated lenses. Results from theoretical analysis and real experiments show that the proposed method is more efficient and accurate than the conventional circular aperture approach.
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