A class invariant must hold before and after all method calls (once the object is constructed).
类在方法调用之前和之后必须保持不变(一旦对象已经构建)。
Similarly, field-invariant tests are never evaluated during object construction, but they are evaluated after construction completes.
类似地，字段的不变条件测试从不在对象构造期间进行，但是它们会在构造完成之后进行。
This paper presents a novel object tracking method based on SIFT(scale invariant feature transform) feature matching.
提出一种基于尺度不变特征变换（SIFT）特征匹配的目标跟踪方法。
This representation is invariant to the translation, rotation, and scaling change of the object.
这种表示是客体平移、旋转和相似变化的不变量。
Object invariant describes the relationship of the object-oriented data structure, it always holds true after the object creation and on the entrance and exit of the method invocation.
对象不变式描述了面向对象数据结构中元素间的关系，在对象创建后以及方法引用前后它总为真。
A 2d object recognition algorithm based on geometry invariant and BP Network.
提出了一种基于几何不变性和BP网络的二维目标识别算法。
The algorithm can adapt to object recognition, invariant not only under rotation? Scaling? Translation, but under affine and projective transformation.
算法不仅能适应目标物体在旋转、缩放、平移变换下的不变性识别。而且能适应仿射及射影变换下的不变性识别。
A video object watermark algorithm using Scale-Invariant feature Transform (SIFT) features and video segmentation based on spatiotemporal information is proposed.
提出一种结合尺度不变特征变换(SIFT)特征点校正和时空域视频对象分割的视频对象水印算法。
SIFT has proved to be the most robust local invariant feature descriptor in object recognition and matching.
目前，SIFT已经被证明鲁棒性最好的局部不变特征描述符。
In this paper a method of the three-dimensional object recognition with rotation-invariant based on moire fringe is proposed.
本文提出一种基于莫尔条纹的三维物体旋转不变识别方法。
Object invariant is important in the object-oriented program proof.
对象不变式在面向对象程序的证明中具有重要作用。
Moreover, by extracting shape invariant moment characteristics of object region, this paper also presents a BP neural network based object recognition method.
对分割后的目标，提取不变矩特征，然后利用人工神经网络实现了运动目标的快速识别。
The recognition of object figure is by invariant moments.
目标图像的形状识别采用基于图形的不变矩理论。
For boosting up the feature's discriminating ability, both scale invariant features and kernel based color distribution features are used as descriptors of tracked object.
为增强跟踪算法区分目标的能力，算法将尺度不变特征和基于核的颜色分布特征统一用作目标的跟踪特征。
It looks for properties on the given object and attempts to load their values out of the invariant culture's resource bundle.
它查找给定对象上的属性并尝试从固定区域性的资源包中加载这些属性的值。
Abstract : The Scale-invariant Feature Transform(SIFT) algorithm was improved in this paper, which could match two pictures and could also compute the object rotation angles in the pictures.
摘要 ：改进了传统的尺度不变特征变换（SIFT）算法，使其在进行图像匹配的同时，可以求取出物体的旋转角度。
Aim a novel method for three-dimensional (3-d) object rotation-invariant recognition is proposed.
目的提出一种对三维物体进行旋转不变识别的新方法。
Serializes the given object into an expression appropriate for the invariant culture.
将给定对象序列化为适合于固定区域性的表达式。
Serializes the given object into an expression appropriate for the invariant culture.
将给定对象序列化为适合于固定区域性的表达式。
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