초록 ▼

A system for detecting and counting individuals in a stationary or moving crowd based on a digital or digitized image captured from a single camera. Initial information is assumed based on a foot-to-head plane homology, where a geometric construct is developed to best enclose image features with a h

A system for detecting and counting individuals in a stationary or moving crowd based on a digital or digitized image captured from a single camera. Initial information is assumed based on a foot-to-head plane homology, where a geometric construct is developed to best enclose image features with a high probability of being an individual within a crowd. These geometric constructs are then subjected to further probabilistic analysis to determine individuals. The vector track of each individual is determined to validate the determination of a group of features as individuals, thereby compensating for occlusion of an individual within any given frame image. A virtual gate is then employed to count the individuals moving past the virtual gate. Also, by weighting portions of the individual, events near the gate can be predicted.

대표청구항 ▼

What is claimed as new and desired to be protected by Letters Patent of the United States is: 1. A method for counting at least one individual in a crowd comprising the steps of: (i) calibrating an image capturing device and an image processing device; (ii) capturing a flame of an image with the im

What is claimed as new and desired to be protected by Letters Patent of the United States is: 1. A method for counting at least one individual in a crowd comprising the steps of: (i) calibrating an image capturing device and an image processing device; (ii) capturing a flame of an image with the image capturing device; the image processing device performing the steps comprising: (iii) drawing a virtual gate through the image; (iv) applying a foreground estimation module to the image; (v) applying a tracking module to the image; (vi) applying a crowd segmentation module to the image to separate the individual from the crowd; (vii) counting the individual; wherein the crowd segmentation module in step (v) comprises the steps of (i) identifying at least one low level image feature; (ii) hypothesizing at least one clique from the low level image features; and (iii) constraining the clique according to a geometric shape model; wherein the constraining of step (iii) comprises: (iv) assigning each low level image feature to a single clique; (v) establishing future assignments according to an assignment vector based on a likelihood function; wherein the likelihood function is a free energy equation. 2. The method of claim 1, wherein the calibration of step (i) utilizes foot-to-head plane homology. 3. The method of claim 1, wherein the tracking module comprises applying the Hungarian algorithm. 4. The method of claim 1, wherein the tracking module and the segmentation module are integrated. 5. The method of claim 1, wherein the individual comprises a person.