多功能的智能家居控制系统

一、项目介绍 智能家居系统产品取代了传统的灯光及家电控制模式，在为您提供安全保障的同时．让您轻松享受生活。在外您可通过电话、电脑来远程遥控您的家居，例如在回家的路上提前打开家中的空凋和热水器；到家开门时，借助门磁或红外传感器，系统会自动为您拉上窗帘、打开过道灯，让家处于最佳的状态迎接您的归来；回到家里，通过遥控器您可以方便地控制房间内的各种电器设备，设置所需的预置场景，让懂得生活的您有更充裕的时间来享受更舒适的生活。     

3ds max光能传递渲染效果图问题分析和解决办法

光能传递渲染是3ds max软件中常用的渲染方法,有五个参数设置要点。初学者在学习和使用时常会出现一些问题。依据近10年的3ds max教学经验,通过对这些问题进行分析,包括灯光设置、光能传递参数、环境设置、材质设置和其他问题,总结了一些解决办法。     

浅析室内效果图中灯光的应用技巧研究

3dsmax是制作室内效果图的必备软件之一,对于室内效果图来讲,室内空间的层次、材质质感的体现等一系列场景氛围的营造都与灯光的设置密不可分,在本文中,笔者将详细地对3dsmax灯光的属性进行分析,并对灯光的应用技巧进行详细的介绍。     

考虑走廊人流影响的建筑火灾人员疏散研究

当前进行的人员疏散研究往往只是单独研究房间内的人员疏散至房间出口的过程,或是单独研究走廊内的人员疏散情况,而很少有将房间与走廊视为整体而进行的研究,研究火灾下房间与走廊整体疏散的情况更是少见。而在实际火灾中,人员并非疏散至房间出口即到达安全状态,往往需要从房间内疏散至走廊尽头的安全出口,此时走廊中的人流会对房间内人员的出口选择以及出口处的拥堵现象的严重程度带来很大影响,所以将房间与走廊视为整体进行疏散研究是很有必要的。对元胞自动机模型进行改进,引进走廊人流方向对于房间内人员路径选择的影响,通过Python建立包含房间与走廊的人员疏散模型,对不同的走廊宽度,房间数量以及房间内的人员密度分别进行模拟,得到火灾下房间与走廊整体的一些疏散特征,特征产生的原因主要是因为走廊人流的方向改变了房间不同出口对于房间内人员的吸引力。     

交互系统在汽车前照灯实训课程开发中的应用

在灯光系统台架上完成汽车前照灯实训,尽管可以锻炼学生电路读图及故障诊断能力,但是对实车灯光系统故障仍然没有概念,实际诊断过程中无从下手,因此,很有必要借助相关教具,在实车上开发灯光系统故障实训课程。汽车线束通断测试盒是一个汽车电路故障设置和测量的交互系统,本文将介绍汽车线束通断测试盒的组成、功能和优点,举例说明如何利用汽车线束通断测试盒在实车上设置各种故障。最后利用汽车线束通断测试盒设置汽车前照灯电路故障,实现汽车前照灯实训课程的开发。     

3ds MAX中灯光使用技巧研究

灯光是3ds MAX软件中模拟光照效果最重要的手段,称得上是3D场景的灵魂。但是在复杂的灯光设置,多变的运用效果中,如何能得到令人满意的照明效果,是困扰3D软件应用者的一大问题。目前国内许多3ds MAX教程中讲述灯光部分较少,为此对场景中灯光的使用方法和应用技巧等进行了研究和具体阐述,给读者以借鉴。     

3DS MAX布光技巧的研究

灯光是3DS MAX中一种特殊的对象,模拟的是光照效果,为了使创建的效果图更贴近现实,就需要在场景中创建灯光对象,并对其颜色、强度等属性进行设置。考虑到渲染速度,创建的灯光宜精不宜多,尽可能使用材质或大气环境模拟光源。     

基于建筑效果图灯光布局的研究

随着信息化时代的到来,计算机技术被普遍的应用在了建筑领域中,推动建筑行业的发展,同时,计算机技术的应用也为建筑效果图的前进提供了良好的契机,提高了建筑效果图所要呈现和渲染的效果。一般建筑效果图在制作时主要涉及材质、建模和灯光三个方面的设计,其中灯光布局是否合理、参数的设置是否得当关系着建筑效果图所要表现的建筑场景效果,因此,本文通过研究建筑效果图的灯管布局,分析各种布局方法的设置技巧,以期提高建筑效果。     

济南阳光100小区智能化家居控制案例解析

项目简介 本项目为济南阳光100小区某四室两厅户型案例。室内装修豪华高贵,包括了安全防范、灯光控制、电器控制、远程控制、电动窗帘,确保主人能够方便的对住所内所有灯光电器等设备进行设置操作和保证住所的安全和舒适。     

3DS MAX室内效果图渲染设置方案

论述了从建模——材质贴图——灯光——渲染设置整个工作流程中特别注意的知识要点,让大家了解室内渲染的设置方案.     

Inverse lighting and photorealistic rendering for augmented reality

We present a practical and robust photorealistic rendering pipeline for augmented reality. We solve the real world lighting conditions from observations of a diffuse sphere or a rotated marker. The solution method is based on l ₁-regularized least squares minimization, yielding a sparse set of light sources readily usable with most rendering methods. The framework also supports the use of more complex light source representations. Once the lighting conditions are solved, we render the image using modern real-time rendering methods such as shadow maps with variable softness, ambient occlusion, advanced BRDF’s and approximate reflections and refractions. Finally, we perform post-processing on the resulting images in order to match the various aberrations and defects typically found in the underlying real-world video.     

Tabletop computed lighting for practical digital photography

We apply simplified image-based lighting methods to reduce the equipment, cost, time, and specialized skills required for high-quality photographic lighting of desktop-sized static objects such as museum artifacts. We place the object and a computer-steered moving-head spotlight inside a simple foam-core enclosure and use a camera to record photos as the light scans the box interior. Optimization, guided by interactive user sketching, selects a small set of these photos whose weighted sum best matches the user-defined target sketch. Unlike previous image-based relighting efforts, our method requires only a single area light source, yet it can achieve high-resolution light positioning to avoid multiple sharp shadows. A reduced version uses only a handheld light and may be suitable for battery-powered field photography equipment that fits into a backpack.     

Inverse lighting design using a coverage optimization strategy

Lighting design is an essential process in computer cinematography, games, architectural design and various other applications for correctly illuminating or highlighting parts of a scene and enhancing storytelling. When targeting specific illumination goals and constraints, this process can be tedious and counter-intuitive even for experienced users and thus automatic, goal-driven methods have emerged for the estimation of a lighting configuration to match the desired result. We present a general automatic approach to such an inverse lighting design problem, where the number of light sources along with their position and emittance are computed given a set of user-specified lighting goals. To this end, we employ a special hierarchical light clustering that operates in the lighting goal coverage domain and overcomes limitations of previous approaches in environments with high occlusion or structural complexity. Our approach is independent of the underlying light transport model and can quickly converge to usable solutions. We validate our results and provide comparative evaluation with the current state of the art.     

Light-Source Modeling Using Pyramidal Light Maps

The diversity of lighting arrangements and fixtures in everyday life allows us great creative and functional control over the appearance of our environments. In computer graphics, the lack of realistic models of light sources does not permit the same level of control. To model a light source, one must (at least) be able to specify its geometry and its spatial intensity distribution. We describe a system that permits the interactive specification of point, linear, and area light sources having arbitrary and variable spatial intensity distributions across their domains. A continuous distribution of an extended light source is created by interpolating a set of sample distributions that are interactively placed on the light source. Rendering is accomplished by resampling the light source at a variable resolution. To speed up rendering, a pyramidal representation of the light source is created, allowing the dynamic selection of the resampling rate. We describe the theory, design, and implementation of our light-source modeling system. Pyramidal light-source models can be used in rendering environments such as conventional scanline or ray-tracing renderers, or renderers with programmable shaders.     

Acquiring linear subspaces for face recognition under variable lighting

Previous work has demonstrated that the image variation of many objects (human faces in particular) under variable lighting can be effectively modeled by low-dimensional linear spaces, even when there are multiple light sources and shadowing. Basis images spanning this space are usually obtained in one of three ways: a large set of images of the object under different lighting conditions is acquired, and principal component analysis (PCA) is used to estimate a subspace. Alternatively, synthetic images are rendered from a 3D model (perhaps reconstructed from images) under point sources and, again, PCA is used to estimate a subspace. Finally, images rendered from a 3D model under diffuse lighting based on spherical harmonics are directly used as basis images. In this paper, we show how to arrange physical lighting so that the acquired images of each object can be directly used as the basis vectors of a low-dimensional linear space and that this subspace is close to those acquired by the other methods. More specifically, there exist configurations of k point light source directions, with k typically ranging from 5 to 9, such that, by taking k images of an object under these single sources, the resulting subspace is an effective representation for recognition under a wide range of lighting conditions. Since the subspace is generated directly from real images, potentially complex and/or brittle intermediate steps such as 3D reconstruction can be completely avoided; nor is it necessary to acquire large numbers of training images or to physically construct complex diffuse (harmonic) light fields. We validate the use of subspaces constructed in this fashion within the context of face recognition.     

Error analysis of surface normals determined by radiometry

Surface normals can be computed from three images of a workpiece taken under three distinct lighting conditions without requiring surface continuity. Radiometric methods are susceptible to systematic errors such as: errors in the measurement of light source orientations; mismatched light source irradiance; detector nonlinearity; the presence of specular reflection or shadows; the spatial and spectral distribution of incident light; surface size, material, and microstructure; and the length and properties of the light source to target path. Typically, a 1° error in surface orientation of a Lambertian workpiece is caused by a 1 percent change in image intensity due to variations in incident light intensity or a 1° change in orientation of a collimated light source. Tests on a white nylon sphere indicate that by using modest error prevention and calibration schemes, surface angles off the camera axis can be computed within 5°, except at edge pixels. Equations for the sensitivity of surface normals to major error sources have been derived. Results of surface normal estimation and edge extraction experiments on various non-Lambertian and textured workpieces are also presented.     

Determining Generative Models of Objects Under Varying Illumination: Shape and Albedo from Multiple Images Using SVD and Integrability

We describe a method of learning generative models of objects from a set of images of the object under different, and unknown, illumination. Such a model allows us to approximate the objects' appearance under a range of lighting conditions. This work is closely related to photometric stereo with unknown light sources and, in particular, to the use of Singular Value Decomposition (SVD) to estimate shape and albedo from multiple images up to a linear transformation (Hayakawa, 1994). Firstly we analyze and extend the SVD approach to this problem. We demonstrate that it applies to objects for which the dominant imaging effects are Lambertian reflectance with a distant light source and a background ambient term. To determine that this is a reasonable approximation we calculate the eigenvectors of the SVD on a set of real objects, under varying lighting conditions, and demonstrate that the first few eigenvectors account for most of the data in agreement with our predictions. We then analyze the linear ambiguities in the SVD approach and demonstrate that previous methods proposed to resolve them (Hayakawa, 1994) are only valid under certain conditions. We discuss alternative possibilities and, in particular, demonstrate that knowledge of the object class is sufficient to resolve this problem. Secondly, we describe the use of surface consistency for putting constraints on the possible solutions. We prove that this constraint reduces the ambiguities to a subspace called the generalized bas relief ambiguity (GBR) which is inherent in the Lambertian reflectance function (and which can be shown to exist even if attached and cast shadows are present (Belhumeur et al., 1997)). We demonstrate the use of surface consistency to solve for the shape and albedo up to a GBR and describe, and implement, a variety of additional assumptions to resolve the GBR. Thirdly, we demonstrate an iterative algorithm that can detect and remove some attached shadows from the objects thereby increasing the accuracy of the reconstructed shape and albedo.     

A common type of commercially available LED light source allows for colour discrimination performance at a level comparable to halogen lighting

Abstract

As light sources based on light emitting diodes (LED) are increasingly used to replace classic tungsten-based light sources in household lighting applications, possible impairments of colour perception under those light sources due to a different spectral power distribution become a major concern. The Colour Rendering Index (CRI) which is the only measure available to the end user is controversial and does not represent a comprehensive measure of colour perception. Aspects of colour perception disregarded by the CRI such as colour discrimination have to be taken into account as well. Therefore, we evaluated colour discrimination performance under a commercially available phosphor-converted LED light source from a popular brand (OSRAM) in comparison to a classic tungsten-based halogen light source. Colour discrimination performance was not affected by the type of light source, indicating that the phosphor-converted LED light source enables colour discrimination performance comparable to that of halogen lighting despite being associated with a lower CRI.

Practitioner summary: Considering the increasing use of energy efficient light sources, we compared colour discrimination under a common type of phosphor-converted LED and under traditional halogen lighting. Colour discrimination performance was comparable in both lighting conditions, indicating that the phosphor-converted LED can replace halogen lighting without sacrificing colour discrimination for energy efficiency.

Abbreviations: LED: light emitting diode; CRI: colour rendering index; CCT: correlated colour temperature; CIE: commission internationale de l’éclairage; FMHT: Farnsworth-Munsell 100-Hue Test; lm: lumen; lx: lux, lumen/m^2; W: watt; nm: nanometer; K: kelvin