B movie

A B movie is a low-budget commercial motion picture that is not an arthouse film. In its original usage, during the Golden Age of Hollywood, the term more precisely identified a film intended for distribution as the less-publicized, bottom half of a double feature. Although the U.S. production of movies intended as second features largely ceased by the end of the 1950s, the term B movie continued to be used in the broader sense it maintains today. In its post–Golden Age usage, there is ambiguity on both sides of the definition: on the one hand, the primary interest of many inexpensive exploitation films is prurient; on the other, many B movies display a high degree of craft and aesthetic ingenuity.

In either usage, most B movies represent a particular genre—the Western was a Golden Age B movie staple, while low-budget science-fiction and horror films became more popular in the 1950s. Early B movies were often part of series in which the star repeatedly played the same character. Almost always shorter than the top-billed films they were paired with, many had running times of 70 minutes or less. The term connoted a general perception that B movies were inferior to the more handsomely budgeted headliners; individual B films were often ignored by critics.

Feature

A feature is a distinct property or piece, which may refer to:

Science and technology

Media

Feature (computer vision)

In computer vision and image processing, a feature is a piece of information which is relevant for solving the computational task related to a certain application. This is the same sense as feature in machine learning and pattern recognition generally, though image processing has a very sophisticated collection of features. Features may be specific structures in the image such as points, edges or objects. Features may also be the result of a general neighborhood operation or feature detection applied to the image.

Other examples of features are related to motion in image sequences, to shapes defined in terms of curves or boundaries between different image regions, or to properties of such a region.

The feature concept is very general and the choice of features in a particular computer vision system may be highly dependent on the specific problem at hand.

Introduction

When features are defined in terms of local neighborhood operations applied to an image, a procedure commonly referred to as feature extraction, one can distinguish between feature detection approaches that produce local decisions whether there is a feature of a given type at a given image point or not, and those who produce non-binary data as result. The distinction becomes relevant when the resulting detected features are relatively sparse. Although local decisions are made, the output from a feature detection step does not need to be a binary image. The result is often represented in terms sets of (connected or unconnected) coordinates of the image points where features have been detected, sometimes with subpixel accuracy.

Distinctive feature

In linguistics, a distinctive feature is the most basic unit of phonological structure that may be analyzed in phonological theory.

Distinctive features are grouped into categories according to the natural classes of segments they describe: major class features, laryngeal features, manner features, and place features. These feature categories in turn are further specified on the basis of the phonetic properties of the segments in question.

Since the inception of the phonological analysis of distinctive features in the 1950s, features traditionally have been specified by binary values to signify whether a segment is described by the feature; a positive value, [+], denotes the presence of a feature, while a negative value, [−], indicates its absence. In addition, a phoneme may be unmarked with respect to a feature. However, in recent developments to the theory of distinctive features, phonologists have proposed the existence of single-valued features. These features, called univalent or privative features, can only describe the classes of segments that are said to possess those features, and not the classes that are without them.