CN105308650A - 具有来自分开的图像的自适应支持权重的主动立体 - Google Patents
具有来自分开的图像的自适应支持权重的主动立体 Download PDFInfo
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Abstract
本公开涉及基于主动照明的立体匹配,包括使用未主动照明的图像中的块来获得权重,该权重被用于被主动照明的立体图像中的块相似度确定。为了将被主动照明的立体图像中的像素相关联,自适应支持权重计算可被用于确定对应于各像素的块的相似度。为了获得对于自适应支持权重计算有意义的自适应支持权重,通过处理未主动照明的(“干净”)图像来获得权重。
Description
背景
一种用立体的一对图像来执行深度估计的方法是通过将一幅图像的小图像块与另一图像的块作比较来寻找它们之间的对应关系。为了测量一幅图像中的像素p与另一图像中的像素q匹配得有多好,使用诸如经标准化的互相关(NCC)或经平方的差之和(SSD)之类的匹配分数来将以p为中心的块与以q为中心的块作比较。
例如,左图像IL中的像素p处的块与右图像IR中的像素q处的块之间的(负的)SSD计算为
其中r是块的半径;(负号被使用,使得相似的块得到高分数,而不相似的块得到低分数)。
为了确保这一匹配分数对于正确的匹配是高的,而对于所有其它可能的匹配是低的,可对场景施加主动照明图案(例如,伪随机激光点组成的图案)。这确保这些块包含一些独有的纹理。为了使得该主动照明对于人类不可见,该主动照明和立体相机可工作在波谱的红外(IR)区域中,而不是可见光部分。
基于块的立体照片所具有的一个问题是靠近深度间断点(例如,在物体边界处)的像素可能得到不正确的深度估计,这是由于块可能包括来自两个不同深度的像素的现实(有时被称为“立体增胖”)。对于实际深度为z1但是位于靠近深度为z2的物体的像素p,该块可能包括既来自z1又来自z2的像素。如果块中的z2像素具有比z1像素更强的纹理,则z2的匹配分数可能比z1的匹配分数更高,尽管实际深度是z1。这导致像素p得到不正确的深度估计z2。
为了在其它块匹配场合中消除这一效应,一种流行的方法是基于块中的每一个像素是否被认为处于与感兴趣的像素p相同的深度来为该像素分配一个权重。具有与p相同深度的块的各部分应当得到高权重,而具有不同深度的部分应当得到低权重。在计算NCC或SSD时,块的不同部分的贡献被加权。这一方法一般被称为“自适应支持权重”(ASW)。
由于块中的各像素的深度是未知的,权重通过仅查看输入图像来计算。ASW方法背后潜在的假设是在用IR或RGB(可见光谱)相机在没有主动图案化照明的情况下捕捉的图像中,块中具有相似深度的像素一般具有相似颜色。因此,一种简单的计算块中的每个像素的权重的方法是将其颜色与中心像素p的颜色作比较。具有类似于中心像素的颜色的像素得到高权重,而具有不同颜色的像素得到低权重。使用以上的SSD匹配分数中的这些权重,计算是:
权重wij可以通过将块像素与中心像素作比较来从左图像中计算:
其中λ是标量参数。
通过主动照明对IR图像计算自适应支持权重所具有的问题是图案化的照明打破了表面的颜色将大致恒定的假设。照明图案导致到处发生大的强度/颜色变化(不仅仅在物体边界处),由此立体匹配退化。
概述
提供本概述以便以简化形式介绍将在以下的详细描述中进一步描述的一些代表性概念的选集。本概述不旨在标识出所要求保护的主题的关键特征或必要特征,也不旨在以限制所要求保护的主题的范围的任何方式来使用。
简单来说,此处描述的主题的各方面中的一个或多个涉及使用来自未主动照明的图像的权重来确定被主动照明的立体图像中的像素匹配的块相似度。一个或多个方面涉及处理多幅图像,所述多幅图像包括被主动照明的立体图像和未主动照明的图像。处理包括为所述未主动照明的图像中对应于所述被主动照明的立体图像中的块的块确定权重,在其中,每一个块基于所述图像中的一幅图像中的参考像素。支持权重用来确定所述被主动照明的立体图像中的对应块之间的相似度分数。
在一个或多个方面,图像处理组件包括与所述图像捕捉组件耦合的匹配算法,所述图像捕捉组件捕捉多幅图像,所述多幅图像包括被主动照明的立体图像,以及未主动照明的图像。所述图像处理组件被配置成处理所述多幅图像,包括经由所述匹配算法来处理所述多幅图像。所述匹配算法处理所述未主动照明的图像中的块以确定对应于所述块中的像素的权重,以及使用所述权重来确定所述被主动照明的图像中的对应块之间的相似度。
一个或多个方面涉及接收被主动照明的立体红外(IR)图像和接收未主动照明的图像。获得所述未主动照明的图像中的块的自适应支持权重。自适应支持权重被用于自适应支持权重计算以确定被主动照明的立体IR图像中的对应块的相似度。
结合附图阅读以下详细描述,本发明的其他优点会变得显而易见。
附图简述
作为示例而非限制,在附图中示出了本发明,附图中相同的附图标记指示相同或相似的元素,附图中:
图1是根据一个或多个示例实现的表示可被用来投影和捕捉主动照明的图像和未主动照明的图像的示例组件的框图。
图2表示了根据一个或多个示例实现的处理图像以基于从未主动照明的图像中获得的权重来确定主动照明的图像中的块的相似度。
图3表示了根据一个或多个示例实现的被布置为捕捉被主动照明的立体RGB图像的可见光(RGB)相机和被布置为捕捉未主动照明的图像的红外(IR)相机。
图4表示了根据一个或多个示例实现的被布置为捕捉被以IR光谱的一部分主动照明的立体IR图像的红外(IR)相机,以及被布置为具有陷波滤波器以捕捉未主动照明的图像的IR相机。
图5表示了根据一个或多个示例实现的捕捉被主动照明的立体图像和未主动照明的图像的相机,其中一个相机生成被主动照明的立体图像和未主动照明的图像中的一个。
图6是根据一个或多个示例实现的表示涉及使用来自未主动照明的图像的权重来处理被主动照明的立体图像的示例步骤的流程图。
图7是表示其中可实现在本文中所描述的各实施例的一个或多个方面的游戏系统形式的示例性、非限制性计算系统或操作环境的框图。
详细描述
此处所描述的技术的各个方面一般涉及使用未主动照明的图像来提供正被处理以寻找其中匹配的像素的两个被主动照明的立体图像的自适应支持权重。例如,第三相机可被用经由来自不同于捕捉到的立体图像中感测到的主动照明光谱(例如,红外的)的光谱(例如可见光)的一部分的光来捕捉第三(未主动照明的)图像。一般来说,在未主动照明的图像中,主动照明图案是不可见的,由此具有相似深度的像素具有相似的颜色这一普遍假设保持为真。因此,对于在主动照明的立体图像中被评估的任何像素,可基于未主动照明的图像中的对应像素和其块中的像素之间的相似度(例如,颜色相似度)来确定自适应支持权重。因此,自适应支持权重能够被用在主动立体图像匹配中。
应当理解,本文中的任何示例均是非限制的。因此,本发明不限制于本文所述的任何具体的实施例、方面、概念、结构、功能或示例。相反,此处所描述的实施例、方面、概念、结构、功能或示例中的任一个都是非限制性的,并且本发明一般能够以在主动深度感测以及图像处理中提供益处和优点的各种方式来使用。
图1示出了捕捉立体IR图像和RGB图像的示例系统,在其中具有立体IR相机101和102、立体RGB相机103和104、以及投影仪106(例如衍射成数千个点的IR激光器)。需要注意,这仅仅是一个示例布置,并且在其他布置中,相机101-104可以按照相对于彼此的任何次序来布置。例如,RGB相机中的一个和IR相机中的一个可共享一个光路;另一个RGB和另一个IR相机可类似地这样做。在其它布置中,仅存在一个RGB相机。作为又一示例,投影仪可被放置在相机之上。此外,任何相机和/或投影仪可以彼此物理地分开,而非作为任何固定配置的一部分。因而,图1是仅出于解说的目的来示出各个示例组件,并且不应从图1推断出外壳/群设备等等内的设备的规模、相对尺寸、相对位置、组合等。
在图1的示例中,相机101-104以及投影仪106耦合到图像捕捉系统或子系统108(或与其组合)。相机一般例如经由相机接口110和控制器111来控制以捕捉在时间上同步的立体图像(例如,相机被“同步锁定”)。在一个实现中,相机101和102捕捉红外(IR)图像114,因为IR在变化的光条件下在深度估计方面高度有效并且不影响场景的可视外观。此外,相机103和104捕捉与IR图像同步锁定的立体RGB图像115。
在图1中,示出了将诸如点(例如,圆点)的图案或线图案等IR图案投影到场景上的投影仪106,但可以使用其他点形状和/或图案类型。出于简明的目的,圆点在下文概括地描述。通过用相对大量的分布式红外圆点照亮场景,IR相机102和103捕捉纹理数据作为红外图像数据的一部分。注意,投影仪106被示为经由投影仪接口116耦合到控制器112;任何此类控制可以与如打开或关闭投影仪或者使用节能模式那样简单,然而,更复杂的控制(诸如脉冲、改变圆点分布、改变强度等)也是可行的。
相机101-104捕捉到的图像被提供给图像处理系统或子系统118。在一些实现中,图像处理系统118和图像捕捉系统或子系统104或其各部分可被组合成单个设备。例如,家庭娱乐设备可包括图1中所示的所有组件(以及其他未示出的组件)。在其他实现中,图像捕捉系统或子系统104的各部分(或全部),如相机和投影仪,可以是耦合到游戏控制台、个人计算机、移动设备、、专用处理设备等的分开的设备。
图像处理系统或子系统118包括处理器120和包含一个或多个图像处理算法的存储器122,图像处理算法包括此处所描述的立体匹配算法124。这可以是硬件逻辑、固件和/或软件的形式。一般来说,在一个实现中,立体匹配算法124确定左IR图像中的哪些圆点与右IR图像中的哪些圆点相关,(框130)由此可通过进一步处理匹配的圆点之间的差异来确定深度数据;因而可计算深度图。
图1中还示出了到图像处理系统或子系统118的接口132,如用于连接键盘、游戏控制器、显示器、定点设备、用于语音命令的话筒等,以适于供用户与应用等进行交互。
需要注意,经校准的投影仪可被视为相机。换言之,如果被投影的图案是已知的,并且投影仪是经校准的(例如,其位置/朝向/焦距等是已知的),则已知的投影仪图像(如此处所使用的,该已知的投影仪图像被认为是捕捉的图像)和主动照明的相机图像之间的基于块的立体(如在此所述的)可使用从未主动照明的图像中计算的自适应支持权重来计算。因此,替代系统可包括一个经校准的投影仪、一个用于捕捉被主动照明的图像的相机、以及一个用于捕捉未主动照明的图像的相机。
图2例示出匹配算法124的各方面。在一个实现中,匹配算法处理左IR图像101、右IR图像102以及RGB图像103以确定左和右IR图像101和102之间的像素匹配数据222。如此处所描述的,匹配算法124从RGB图像203(例如左图像,如果立体RGB图像可用的话)中提取块权重。
更具体地,在计算左图像210(也称为IL)中的像素p和右图像201(也称为IR)中的像素q之间的匹配分数时,并且三个相机之间的相对位置和朝向已知时,如果p和q确实匹配的话,第三图像203(也称为IW)中的像素(记为s)的位置处的对应点将会是可见的。匹配算法124计算p和q附近的块223和224之间的加权匹配分数,其中从第三图像(标记为IW)中的s附近的块225中提取权重228:
其中λ是标量参数。
块225的不同部分的贡献因而基于块225中的其它像素与像素s的相似度(例如颜色)来加权。这些权重228可像是从被主动照明的图像中提取出那样地被使用,即它们在例如基于传统的自适应支持权重技术来计算NCC或SSD时被使用,除了被外部确定的权重之外。需要注意,NCC可受益于具有与正用那些权重来处理的块解耦的权重。
采用像素匹配数据222,进一步的立体深度处理230可确定深度图232。例如,匹配的像素之间的一个或多个特征中的差异(例如与三角测量一起)可被用于确定深度。
在一个实现中,左图像的像素p被选择作为参考像素,而右图像202沿行扫描以寻找候选的q像素以找出最佳匹配,而图像103中的s像素随着扫描进程被重新确定。尽管如此,在其它实现中这可被反向,例如左图像可被扫描,而右图像被用作为参考点。
在另一替换实施例中,未主动照明的图像203中的像素(例如,像素s)可被选择作为参考点。在这种情形下,左图像201和右图像202两者可分别被同时处理以基于自适应支持权重技术来寻找匹配的像素。
如可容易理解的,各种可能的其它相机组合可受益于此处所描述的技术。例如,取代图2中的配置(其中立体IR相机用RGB相机来捕捉立体图像以为图像提供自适应支持权重),在图3中,立体RGB相机330、331可捕捉用可见光来照明的图像332、333,其中IR相机334被用于为图像335提供自适应支持权重。图3中还表示了RGB投影仪336。
另一替换实施例是使用滤波,如图4中一般表示的。例如,立体IR相机440和441可分别捕捉被主动照明的图像442和443。另一IR相机444,其中该另一IR相机具有陷波滤波器446以移除光谱中包含主动照明的部分,并由此为未主动照明图像445提供自适应支持权重。图3中还表示了IR投影仪448。
也可以使用时间分段。例如,相同的相机可捕捉一个被主动照明的帧,随后接着一个未主动照明的帧。如果帧速率相对于被捕捉的场景中的任何运动足够得快,则像素匹配可基于使用从未主动照明的帧中提取的权重。
转至另一方面,此处所例示的方程式以结合三相机设置的简单形式来给出,其中使用在三幅图像中具有相同块大小的正方形块。在现实中,来自一幅图像的正方形块在另两幅图像中会看上去变形,并且还可能具有不同的大小。然而,该变形和大小差异可以已知方式来补偿,并且一般来说,基本概念是相同的。
尽管如此,为了减少这类效应,在另一方面,两个相机可共享相同的光路,一个用来捕捉被主动照明的图像,而另一个用来捕捉未主动照明的图像。采用相同的光路简化了计算,例如图2中示出的p和s像素(或者q和s像素)在其相应图像中具有相同位置,并且那两个像素的块也将是相同大小和形状。共享光路可通过例如反射来实现。
作为另一替代实施例,通过让一个配备有光学元件/滤波的相机来提供分开的图像,光路可以对于被主动照明的图像和未主动照明的图像是相同的。因此,替代第三相机是从相对于立体配对的一个或两个相机不同的视角捕捉图像的独立的物理设备,“第三”相机可以被集成在立体相机中的一个中,使得从相同的视角捕捉不同照明的图像。例如,如在图5中,立体相机中的一个(例如,左相机550)可包括用于将传入光在两个传感器之间拆分的机构552,其中每个传感器具有不同的光谱响应,从而提供两幅图像(一个具有主动照明的图像554和一个不具有主动照明的图像556)以用于与另一(例如右相机558的)图像559进行匹配。
替代地,机构552表示立体相机中在像素上具有Bayer图案的那一个立体相机,由此一些像素得到包括主动照明的光,而另一些没有。对于这样的单个传感器,生成用于与另一(例如,右相机558)图像559进行匹配的两幅图像(一个具有主动照明的图像554和一个不具有主动照明的图像556)是有可能的。
图6概述了与如此处所描述的从第三图像中提取权重有关的一般方面,开始于步骤602,在此图像被捕捉,例如使用以上所描述的技术中的任意一种。步骤604选择参考像素(例如,在左图像中)并确定其周围的块。步骤606选择另两幅图像中的相应像素/块(例如作为在右图像中沿行扫描的一部分),并且基于参考像素和被选择用于评估的像素来确定未主动照明图像中的像素。
使用未主动照明的图像中的块来确定权重,例如基于块中的其它像素与中心像素的颜色相似度。这些权重在步骤610中被用来计算被主动照明的图像中的块相似度分数。
步骤612重复过程(例如,线性地扫描像素),直到获得可能匹配的像素的基于块的相似度分数。最高分数可被用来确定与参考像素匹配的像素,该像素在步骤614被输出作为匹配的配对的一部分。
需要注意,虽然颜色相似度被用作为一种用于确定相对权重的度量,其它类型的相似度也可被使用。例如,其它捕捉的数据可包括纹理数据。作为一个示例,纹理可被用作为一种使用大的块来确定可能的相似度的度量。如果不足够相似,新的像素/块被选择作为匹配的候选,依此类推。然而,如果足够相似,则可使用放大的块,诸如如此处所描述的用颜色相似度来确定权重。这可以更大的块处理和多级块匹配为代价来提高像素匹配中的准确性。
示例性操作环境
可以容易地理解以上所描述的实施方式及其替换方式可实现在任何合适的计算设备上,包括游戏系统、个人计算机、平板电脑、DVR、机顶盒、智能电话等。当多个这样的设备被链接在一起时,这样的设备的组合也是可行的。为了描述的目的,以下描述了一个游戏(包括媒体)系统作为一个示例性操作环境。
图7是示例游戏和媒体系统700的功能框图并且更详细地示出各功能组件。控制台701具有中央处理单元(CPU)702以及便于处理器访问各种类型的存储器的存储器控制器703,各种类型的存储器包括闪存只读存储器(ROM)704、随机存取存储器(RAM)706、硬盘驱动器708,以及便携式媒体驱动器709。在一种实现中,CPU702包括1级高速缓存710和2级高速缓存712,这些高速缓存用于临时存储数据并因此减少对硬盘驱动器进行的存储器访问周期的数量,从而提高了处理速度和吞吐量。
CPU702、存储器控制器703、以及各种存储器设备经由一个或多个总线(未示出)互连。在此实现中所使用的总线的细节对理解此处所讨论的关注主题不是特别相关。然而,应该理解,这样的总线可以包括串行和并行总线、存储器总线、外围总线、使用各种总线体系结构中的任何一种的处理器或局部总线中的一个或多个。作为示例,这样的架构可以包括工业标准体系结构(ISA)总线、微通道体系结构(MCA)总线、增强型ISA(EISA)总线、视频电子标准协会(VESA)局部总线、以及也称为夹层总线的外围部件互连(PCI)总线。
在一个实现中,CPU702、存储器控制器703、ROM704以及RAM706被集成到公用模块714上。在此实现中,ROM704被配置为经由外围部件互联(PCI)总线或类似的总线以及ROM总线(两者都未示出)或类似的连接到存储器控制器703的闪存ROM。RAM706被配置为多个双倍数据速率同步动态RAM(DDRSDRAM)模块,它们被存储器控制器703通过分开的总线(未示出)独立地进行控制。硬盘驱动器708和便携式媒体驱动器709被示为通过PCI总线和AT附加(ATA)总线716连接到存储器控制器703。然而,在其他实现中,也可以备选地应用不同类型的专用数据总线结构。
三维图形处理单元720和视频编码器722构成了视频处理流水线,用于进行高速度和高分辨率(例如,高清晰度)图形处理。数据通过数字视频总线(未示出)从图形处理单元720传输到视频编码器722。音频处理单元724和音频编解码器(编码器/解码器)726构成了对应的音频处理流水线,用于对各种数字音频格式进行多通道音频处理。通过通信链路(未示出)在音频处理单元724和音频编解码器726之间传送音频数据。视频和音频处理流水线向A/V(音频/视频)端口728输出数据,以便传输到电视机或其它显示器/扬声器。在例示出的实施方式中,视频和音频处理组件720、722、724、726以及728被安装在模块714上。
图7示出了包括USB主控制器730和网络接口(NWI/F)732的模块714,网络接口732可包括有线和/或无线组件。USB主控制器730被示为通过总线(例如,PCI总线)与CPU702和存储器控制器703进行通信,并作为外围控制器734的主机。网络接口732提供对网络(例如,因特网、家庭网络等)的访问并且可以是包括以太网卡或接口模块、调制解调器、蓝牙模块、电缆调制解调器等的各种不同的有线和无线接口组件中的任何一种。
在图7中描绘的示例实现中,控制台701包括用于支持四个游戏控制器741(1)-741(4)的控制器支持子部件740。控制器支持子部件740包括支持与诸如,例如,媒体和游戏控制器之类的外部控制设备的有线和/或无线操作所需的任何硬件和软件组件。前面板I/O子部件742支持电源按钮743、弹出按钮744,以及任何其它按钮和任何LED(发光二极管)或暴露在控制台701的外表面上的其它指示器等多个功能。子部件740和742经由一个或多个线缆子部件746或类似的与模块714通信。在其他实现中,控制台701可以包括另外的控制器子组件。所示出的实现还示出了被配置为发送和接收可传递给模块714的信号(例如来自遥控器749)的光学I/O接口748。
存储器单元(MU)750(1)和750(2)被示为可以分别连接到MU端口“A”752(1)和“B”752(2)。每一个MU750都提供附加存储,在其上面可以存储游戏、游戏参数、及其它数据。在一些实现中,其他数据可以包括数字游戏组件、可执行的游戏应用,用于扩展游戏应用的指令集、以及媒体文件中的一个或多个。当被插入到控制台701中时,每个MU750可由存储器控制器703访问。
系统供电模块754向游戏系统700的组件供电。风扇756冷却控制台701内的电路。
包括机器指令的应用760被通常存储在硬盘驱动器708上。当控制台701通电时,应用760的各个部分被加载到RAM706和/或高速缓存710和712中以供在CPU702上执行。总得来说,应用760可包括一个或多个程序模块,用于执行各种显示功能,诸如控制对话屏幕供呈现在显示器上(例如,高分辨率监视器)、基于用户输入控制事务以及控制控制台701和外部连接的设备之间的数据传输和接收。
可以通过简单地将系统连接到高分辨率监视器、电视机、视频投影仪、或其它显示设备来将游戏系统700用作独立系统。在此独立模式下,游戏系统700允许一个或多个玩家玩游戏或欣赏数字媒体,例如观看电影或欣赏音乐。然而,随着宽带连接的集成通过网络接口732而成为可能,游戏系统700还可以作为更大的网络游戏社区或系统中的参与组件来操作。
结语
尽管本发明易于作出各种修改和替换构造,但其某些说明性实施例在附图中示出并在上面被详细地描述。然而应当了解,这不旨在将本发明限于所公开的具体形式,而是相反地,旨在覆盖落入本发明的精神和范围之内的所有修改、替换构造和等效方案。
Claims (10)
1.一种方法,包括:
处理多幅图像,所述多幅图像包括被主动照明的立体图像和未主动照明的图像;
为所述未主动照明的图像中对应于所述被主动照明的立体图像中的块的块确定权重,在其中,每一个块基于所述图像中的一幅图像中的参考像素;以及
使用支持权重来确定所述被主动照明的立体图像中的对应块之间的相似度分数。
2.如权利要求1所述的方法,其特征在于:
a)所述图像是用红外(IR)光主动照明的场景的图像,并且其中捕捉所述未主动照明的图像包括捕捉所述场景作为可见光谱图像,或者
b)所述图像是用可见光谱光主动照明的场景的图像,并且其中捕捉所述未主动照明的图像包括捕捉所述场景作为红外图像,或者
c)所述图像是用红外光谱中的一部分中的红外光主动照明的场景的图像,并且其中捕捉所述未主动照明的图像包括使用陷波滤波器来用所述光谱的包含被移除的主动照明的那部分来捕捉所述场景。
3.如权利要求1所述的方法,其特征在于,捕捉所述多幅图像包括经由相同光路捕捉一幅被主动照明的立体图像和未主动照明的图像,或者使用一个相机来捕捉一帧中的被主动照明的立体图像并且捕捉另一帧中的未主动照明的图像,或者以上两者。
4.一种系统,包括,图像处理组件,所述图像处理组件包括与所述图像处理组件耦合的匹配算法,所述匹配算法捕捉多幅图像,所述多幅图像包括被主动照明的立体图像,以及未主动照明的图像,所述图像处理组件被配置成处理所述多幅图像,包括经由所述匹配算法来处理所述多幅图像,所述匹配算法被配置成处理所述未主动照明的图像中的块以确定对应于所述块中的像素的权重,以及使用所述权重来确定所述被主动照明的图像中的对应块之间的相似度。
5.如权利要求4所述的系统,其特征在于,所述匹配算法线性地扫描至少一幅被主动照明的图像中的像素以基于块相似度来寻找匹配像素。
6.如权利要求4所述的系统,其特征在于,所述匹配算法被进一步配置成确定匹配像素数据,并且其中所述匹配算法被耦合到或包含深度处理算法,所述深度处理算法处理所述匹配像素数据以生成深度图。
7.如权利要求4所述的系统,其特征在于:
a)所述被主动照明的立体图像包括红外(IR)图像,并且其中所述未主动照明的图像包括红、绿和蓝(RGB)图像,或者
b)所述被主动照明的立体图像包括RGB图像,并且其中所述未主动照明的图像包括IR图像,或者
c)所述被主动照明的立体图像包括IR图像,并且其中所述未主动照明的图像包括经陷波滤波器滤波的IR图像,所述陷波滤波器移除主动照明。
8.如权利要求4所述的系统,其特征在于,所述图像捕捉组件包括相机,所述相机包括分光机构,所述分光机构被配置成将传入的光分入被主动照明的立体图像和未主动照明的立体图像中的一个。
9.如权利要求4所述的系统,其特征在于,所述相机包括在感测到的像素上的Bayer图案,以便在像素的一个子集上收到包括所述主动照明的光,但在像素的另一子集上收到不包括所述主动照明的光。
10.一个或多个具有可执行指令的计算机可读存储介质或逻辑,所述可执行指令在被执行时执行步骤,步骤包括接收被主动照明的立体红外(IR)图像,接收未主动照明的图像,获得所述未主动照明的图像中的块的自适应支持权重,以及将所述自适应支持权重用于自适应支持权重计算以确定所述被主动照明的立体IR图像中的对应块的相似度。
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