Computer Vision: From Surfaces to 3D Objects
暫譯: 計算機視覺:從表面到三維物體

Tyler, Christopher W.

商品描述

The typical computational approach to object understanding derives shape information from the 2D outline of the objects. For complex object structures, however, such a planar approach cannot determine object shape; the structural edges have to be encoded in terms of their full 3D spatial configuration. Computer Vision: From Surfaces to 3D Objects is the first book to take a full approach to the challenging issue of veridical 3D object representation. It introduces mathematical and conceptual advances that offer an unprecedented framework for analyzing the complex scene structure of the world.

 

 

 

 

 

 

 

An Unprecedented Framework for Complex Object Representation
Presenting the material from both computational and neural implementation perspectives, the book covers novel analytic techniques for all levels of the surface representation problem. The cutting-edge contributions in this work run the gamut from the basic issue of the ground plane for surface estimation through mid-level analyses of surface segmentation processes to complex Riemannian space methods for representing and evaluating surfaces.

 

 

 

 

 

 

 

 

 

State-of-the-Art 3D Surface and Object Representation
This well-illustrated book takes a fresh look at the issue of 3D object representation. It provides a comprehensive survey of current approaches to the computational reconstruction of surface structure in the visual scene.

 

 

商品描述(中文翻譯)

典型的物體理解計算方法是從物體的 2D 輪廓中獲取形狀資訊。然而,對於複雜的物體結構,這種平面方法無法確定物體形狀;結構邊緣必須以其完整的 3D 空間配置進行編碼。《計算機視覺:從表面到 3D 物體》是第一本全面探討真實 3D 物體表示這一挑戰性問題的書籍。它介紹了數學和概念上的進展,提供了一個前所未有的框架,用於分析世界的複雜場景結構。

複雜物體表示的前所未有的框架

本書從計算和神經實現的角度呈現材料,涵蓋了針對所有層次的表面表示問題的新穎分析技術。本書中的尖端貢獻涵蓋了從表面估計的基礎問題(如地面平面)到表面分割過程的中級分析,再到用於表示和評估表面的複雜黎曼空間方法。

最先進的 3D 表面和物體表示

這本插圖豐富的書籍對 3D 物體表示問題進行了全新的探討。它提供了對視覺場景中表面結構計算重建的當前方法的全面調查。

作者簡介

Christopher W. Tyler is the director of the Brain Imaging Center at the Smith-Kettlewell Eye Research Institute. His current research encompasses brain imaging studies and mathematical modeling of the mechanisms of human stereoscopic depth, motion, and face perception as well as higher cognitive processing. He and his team have developed new methods to determine the dynamics of the neural population responses underlying brain imaging signals. By designing stimuli to probe specific neural sub-populations, this new methodology can be used to explore neural properties in the human brain and the changes in neural dynamics during the learning process.

作者簡介(中文翻譯)

克里斯多福·W·泰勒是史密斯-凱特威爾眼科研究所腦成像中心的主任。他目前的研究涵蓋腦成像研究以及人類立體深度、運動和面孔知覺的機制的數學建模,以及更高級的認知處理。他和他的團隊開發了新的方法來確定基於腦成像信號的神經群體反應的動態。通過設計刺激來探測特定的神經子群,這種新方法可以用來探索人腦中的神經特性以及在學習過程中神經動態的變化。