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Image processing method and apparatus |
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Robust multi-modal method for recognizing objects
| Details |
Inventors: Cosatto, Eric; Graf, Hans Peter; Potamianos, Gerasimos;
Assignee: AT&T Corp. (New York, NY)
Primary Examiner: Au; Amelia
Assistant Examiner: Ahmed; Samir
Attorney, Agent or Firm:
A method for tracking heads and faces is disclosed wherein a variety of different representation models can be used to define individual heads and facial features in a multi-channel capable tracking algorithm. The representation models generated by the channels during a sequence of frames are ultimately combined into a representation comprising a highly robust and accurate tracked output. In a preferred embodiment, the method conducts an initial overview procedure to establish the optimal tracking strategy to be used in light of the particular characteristics of the tracking application. |
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DETAILED DESCRIPTION These objects of the invention are accomplished in accordance with the principles of the invention by providing a tracking method which combines a plurality of representation models, together with multiple-channel capability, as needed for improving the accuracy and robustness of the tracked output. By using different types of representation models generated from multiple channels, the method can provide for accurate tracking of heads, faces and facial features under a diverse array of conditions. The method is capable of using different representation models to portray a single feature. Depending on the application, these models may include binary bitmaps (blobs), pixel maps, outlines, moments, bounding boxes, bounding ellipses, position indicators, color information such as in histograms, and other geometric or visual representations which may be suitable for a given application. The analysis is controlled by a model which determines the optimal tracking strategy to be used, depending on the characteristics of the individual and the environment where the images are tracked. Such characteristics may include, for example, lighting, the complexion of the person to be tracked, and other characteristics of the person such as hair color, head orientation, the presence of baldness or large amounts of hair, the presence of beards, moustaches, sunglasses, and other variables. To achieve maximum flexibility, the use of multiple channels can be applied using multiple representation models. In a preferred embodiment, the algorithm is initiated by an overview tracking sequence to determine environmental conditions as well as characteristics of the person to be tracked. Next, based on the results of this overview, the model selects a tracking strategy whereby the optimal representation models and channels are selected to provide for the most accurate and robust tracking result. Once the optimal tracking strategy is determined, the selected channels are activated and the primary tracking process begins
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