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Opportunistic cascade and cascade training, evaluation, and execution for vision-based object detection

机译:机会级联和级联训练,评估和执行,用于基于视觉的对象检测

摘要

The present invention relates to a classifier cascade object detection system. The system operates by inputting an image patch into parallel feature generation modules, each of the feature generation modules operable for extracting features from the image patch. The features are provided to an opportunistic classifier cascade, the opportunistic classifier cascade having a series of classifier stages. The opportunistic classifier cascade is executed by progressively evaluating, in each classifier in the classifier cascade, the features to produce a response, with each response progressively utilized by a decision function to generate a stage response for each classifier stage. If each stage response exceeds a stage threshold then the image patch is classified as a target object, and if the stage response from any of the decision functions does not exceed the stage threshold, then the image patch is classified as a non-target object.
机译:分类器级联对象检测系统技术领域本发明涉及分类器级联对象检测系统。该系统通过将图像补丁输入到并行特征生成模块中来操作,每个特征生成模块可操作用于从图像补丁中提取特征。将特征提供给机会分类器级联,该机会分类器级联具有一系列分类器阶段。机会分类器级联通过在分类器级联中的每个分类器中逐步评估产生响应的特征来执行,决策模块逐渐利用每个响应为每个分类器级生成阶段响应。如果每个阶段响应超过阶段阈值,则将图像补丁分类为目标对象,如果来自任何决策函数的阶段响应未超过阶段阈值,则将图像补丁分类为非目标对象。

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