tailieunhanh - Advances in Human Robot Interaction Part 14

Tham khảo tài liệu 'advances in human robot interaction part 14', kỹ thuật - công nghệ, cơ khí - chế tạo máy phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | 314 Advances in Human-Robot Interaction 9a 9b Fig. 8. Power Spectrum of A at the Base Line Fig. 9. Directional Fourier Transform of A Anticipative Generation and In-Situ Adaptation of Maneuvering Affordance 315 Fig. 10. 2D Agơ Filtering of a Point Image Fig. 11. 2D Power Spectrum of Agơ Filter In 9a the expansion of the roadway is identified with a pattern He F in which scale information c is regulated by the linear diminishing rule from the bottom of the maneuvering affordance d0 to the vanishing point dx . Hence we can conclude that the scope of perception is confined in a probabilistic sense 9b where the estimated distribution -can be utilized as a noisy observation of the self-similarity 1 . 4. Fractal coding of perceptual invariance Via the self-similarity process 1 an attractor point is allocated to satisfy the following constraint with respect to the not-yet-identified contraction mapping Pi e v 10 316 Advances in Human-Robot Interaction where W 9. denotes the fixed point of Hi. By evaluating the attractive force within the framework of the Hausdorff topology Kamejima 1999 we can introduce a simultaneous estimation scheme for model parameters dk 0 9 with non-unique estimates of fixed points associated with not-yet-identified contraction mapping Hj. To apply the articulation scheme 10 with non-deterministic kinetics first a pixel we Q is associated with not-yet-identified attractor s in a stochastic sense. Once we have observed the invariant measure - we can evaluate the probability p w v for capturing unknown fractal attractor s as the solution to the following equation 11 Following this the image plane is partitioned in accordance with the fractal attractor to be detected. Since various types of attractors are simultaneously observed as object images Barnsley 2006 in practical imagery generated information p w v is expanded to cover noisy patterns as confine the distribution into a target attractor let the initial guess for the fixed points 0 1 w be