Image analysis – Applications – Target tracking or detecting
Reexamination Certificate
1998-12-04
2001-10-09
Boudreau, Leo (Department: 2721)
Image analysis
Applications
Target tracking or detecting
C382S117000, C382S118000, C382S190000, C382S209000, C382S276000, C342S090000, C348S169000
Reexamination Certificate
active
06301370
ABSTRACT:
FIELD OF THE INVENTION
The present invention relates to vision-based object detection and tracking, and more particularly, to systems for detecting objects in video images, such as human faces, and tracking and identifying the objects in real time.
BACKGROUND OF THE INVENTION
Recently developed object and face recognition techniques include the use of elastic bunch graph matching. The bunch graph recognition technique is highly effective for recognizing faces when the image being analyzed is segmented such that the face portion of the image occupies a substantial portion of the image. However, the elastic bunch graph technique may not reliably detect objects in a large scene where the object of interest occupies only a small fraction of the scene. Moreover, for real-time use of the elastic bunch graph recognition technique, the process of segmenting the image must be computationally efficient or many of the performance advantages of the recognition technique are not obtained.
Accordingly, there exists a significant need for an image processing technique for detecting an object in video images and preparing the video image for further processing by an bunch graph matching process in a computationally efficient manner. The present invention satisfies these needs.
SUMMARY OF THE INVENTION
The present invention is embodied in an apparatus, and related method, for detecting and recognizing an object in an image frame. The object detection process uses robust and computationally efficient techniques. The object identification and recognition process uses an image processing technique based on model graphs and bunch graphs that efficiently represent image features as jets. The system of the invention is particularly advantageous for recognizing a person over a wide variety of pose angles.
In an embodiment of the invention, the object is detected and a portion of the image frame associated with the object is bounded by a bounding box. The bound portion of the image frame is transformed using a wavelet transformation to generate a transformed image. Nodes associated with distinguishing features of the object defined by wavelet jets of a bunch graph generated from a plurality of representative object images are located on the transformed image. The object is identified based on a similarity between wavelet jets associated with an object image in a gallery of object images and wavelet jets at the nodes on the transformed image.
Additionally, the detected object may be sized and centered within the bound portion of the image such that the detected object has a predetermined size and location within the bound portion and background portions of the bound portion of the image frame not associated with the object prior to identifying the object may be suppressed. Often, the object is a head of a person exhibiting a facial region. The bunch graph may be based on a three- dimensional representation of the object. Further, the wavelet transformation may be performed using phase calculations that are performed using a hardware adapted phase representation.
In an alternative embodiment of the invention, the object is in a sequence of images and the step of detecting an object further includes tracking the object between image frames based on a trajectory associated with the object. Also, the step of locating the nodes includes tracking the nodes between image frames and reinitializing a tracked node if the node's position deviates beyond a predetermined position constraint between image frames. Additionally, the image frames may be stereo images and the step of detecting may include detecting convex regions which are associated with head movement.
Other features and advantages of the present invention should be apparent from the following description of the preferred embodiments, taken in conjunction with the accompanying drawings, which illustrate, by way of example, the principles of the invention.
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Elagin Egor Valerievich
Maurer Thomas
Neven Hartmut
Nocera Luciano Pasquale Agostino
Steffens Johannes Bernhard
Boudreau Leo
Eyematic Interfaces, Inc.
Gray Cary Ware & Freidenrich
Mariam Daniel G.
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