Computer Vision: From Surfaces to 3D Objects

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)

傳統的計算方法對於物體理解是從物體的二維輪廓中獲取形狀信息。然而,對於複雜的物體結構,這種平面方法無法確定物體的形狀;結構邊緣必須以完整的三維空間配置編碼。《從表面到三維物體的計算機視覺》是第一本全面探討真實三維物體表示問題的書籍。它介紹了數學和概念上的創新,為分析複雜場景結構提供了前所未有的框架。

以計算和神經實現的角度呈現材料,本書涵蓋了表面表示問題各個層次的新穎分析技術。這項工作的尖端貢獻從表面估計的基本問題,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,涵蓋了各個方面。

這本圖文並茂的書對三維物體表示問題提出了新的觀點。它全面調查了當前在視覺場景中計算重建表面結構的方法。

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)

Christopher W. Tyler是Smith-Kettlewell Eye Research Institute的腦部影像中心主任。他目前的研究範圍包括腦部影像研究和數學建模,探討人類立體深度、運動和臉部知覺以及更高層次的認知處理機制。他和他的團隊開發了新的方法來確定腦部影像信號背後的神經群體反應動態。通過設計刺激來探測特定神經亞群體,這種新方法可以用於探索人腦中的神經特性以及學習過程中神經動態的變化。