Device and method for judging specific object in multi-angles

Abstract

The invention provides a device for judging a specific object in multi-angles, comprising an input device for inputting image data and multiple cascading sorter groups, wherein each cascading sorter group consists of multiple sorter cascade connections corresponding to a same detection angle; and different sorters are corresponding to different features, each sorter is used for calculating the confidence degree value of the image data in terms of corresponding features when the image data belongs to the specific object detected in a corresponding angle and judging whether the image data belongs to the specific object according to the confidence degree. The device provided by the invention is characterized in that a self-adaption gesture estimation device is arranged between the sorters of the cascading sorter groups and used for judging whether the image data enters the sorters of the detection angle behind the self-adaption gesture estimation device according to the confidence degree value corresponding to the same detection angle and calculated by the sorters before the self-adaption gesture estimation device. The invention also provides a method for judging a specific object in multi-angles.

Description

technical field [0001] The present invention relates to a multi-angle specific object judging device and a multi-angle specific object judging method, more specifically, the present invention relates to a multi-angle specific object that can improve the speed of judging a specific object without affecting the judgment accuracy Judgment equipment and multi-angle specific object judgment method. Background technique [0002] Fast and accurate object detection algorithms are fundamental work for many applications in the field of image processing and video content analysis, such as face detection and emotional state analysis, video conferencing control and analysis, pedestrian protection systems, etc. The Adaboost face detection algorithm can be effectively used for face recognition. There are many products based on this field on the market, such as the face detection function in digital cameras. However, with the rapid development of digital cameras and mobile phones, only fro...

AI Technical Summary

Problems solved by technology

The main disadvantage of this technology is that this method can only be used for the detection of specific objects within a certain range of angles, mainly frontal face recognition, which limits its application to a certain extent.

[0006] Although theoretically a hierarchical classifier structure composed of multiple detection angle classifiers can achieve multi-angle detection problems, the usual multi-angle detection hierarchical classifier structure cannot overcome the following two main problems: (1) due to the increased The number of classifiers increases the judgment time of classifiers, so that the detection speed of the whole detection system is slow and cannot achieve real-time detection; It is the low detection accuracy

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