COMPUTER-VISION BASED SECURITY SYSTEM USING A DEPTH CAMERA

1 .- 8 . (canceled)

9 . A method for securing an environment, comprising:

receiving a two-dimensional (2D) representation of a three-dimensional (3D) environment, wherein the 2D representation is a 2D frame of pixels encoding depth values of the 3D environment, wherein the 2D representation comprises a foreground object, and wherein a background has been removed from the 2D representation;

classifying the foreground object; and

taking an action based on the classification of the foreground object.

10 . The method of claim 9 , wherein classifying the foreground object comprises using a camera-specific classifier.

11 . The method of claim 10 , further comprising:

prior to classifying the foreground object using the camera-specific classifier, training the camera-specific classifier using data samples that are specific to a field of view of a camera with which the camera-specific classifier is associated and data samples that do not include the field of view of the camera.

12 . The method of claim 9 , wherein classifying the foreground object comprises:

associating the foreground object with a category; and

classifying the foreground object as one selected from a group consisting of a threat and a non-threat based, at least in part, on the category.

13 . The method of claim 9 , wherein classifying the foreground object comprises:

making a first determination, by a classifier, that the classification of the foreground object is unknown;

based on the first determination, sending a request to a human operator to classify the foreground object; and

receiving a classification of the object from the human operator.

14 . The method of claim 13 , further comprising:

updating the classifier based on the classification by the human operator.

15 . The method of claim 9 , wherein classifying the foreground object comprises:

sending at least the foreground object to a plurality of portable devices;

receiving a response from at least two of the plurality of portable devices; and

determining the classification of the foreground object based on the responses from the at least two of the plurality of portable devices.

16 . A method for securing an environment, comprising:

receiving a two-dimensional (2D) representation of a three-dimensional (3D) environment, wherein the 2D representation is a 2D frame of pixels encoding depth values of the 3D environment;

identifying a plurality of foreground pixels in the 2D representation;

defining a foreground object based on the plurality foreground pixels;

classifying the foreground object; and

taking an action based on the classification of the foreground object.

17 .- 21 . (canceled)

22 . The method of claim 9 , wherein classifying the foreground object is performed based on at least one feature selected from a group consisting of a geometry of a bounding box associated with the foreground object, a shape of the foreground object, and a motion descriptor of the foreground object.

23 . The method of claim 9 , wherein classifying the foreground object is performed on a set of subsequent frames that comprise the foreground object.

24 . A non-transitory computer readable medium (CRM) comprising instructions that enable a system to:

receive a two-dimensional (2D) representation of a three-dimensional (3D) environment, wherein the 2D representation is a 2D frame of pixels encoding depth values of the 3D environment, wherein the 2D representation comprises a foreground object, and wherein a background has been removed from the 2D representation;

classify the foreground object; and

take an action based on the classification of the foreground object.

25 . The non-transitory CRM of claim 24 , wherein classifying the foreground object comprises using a camera-specific classifier.

26 . The non-transitory CRM of claim 25 , further comprising instructions that enable the system to:

prior to classifying the foreground object using the camera-specific classifier, train the camera-specific classifier using data samples that are specific to a field of view of a camera with which the camera-specific classifier is associated and data samples that do not include the field of view of the camera.

27 . The non-transitory CRM of claim 24 , wherein the instructions for classifying the foreground object comprise functionality to:

associate the foreground object with a category; and

classify the foreground object as one selected from a group consisting of a threat and a non-threat based, at least in part, on the category.

28 . The non-transitory CRM of claim 24 , wherein the instructions for classifying the foreground object comprise functionality to:

make a first determination, by a classifier, that the classification of the foreground object is unknown;

based on the first determination, send a request to a human operator to classify the foreground object; and

receive a classification of the object from the human operator.

29 . The non-transitory CRM of claim 28 , further comprising instructions that enable the system to:

update the classifier based on the classification by the human operator.

30 . The non-transitory CRM of claim 24 , wherein the instructions for classifying the foreground object comprise functionality to:

send at least the foreground object to a plurality of portable devices;

receive a response from at least two of the plurality of portable devices; and

determine the classification of the foreground object based on the responses from the at least two of the plurality of portable devices.

31 . The non-transitory CRM of claim 24 , wherein classifying the foreground object is performed based on at least one feature selected from a group consisting of a geometry of a bounding box associated with the foreground object, a shape of the foreground object, and a motion descriptor of the foreground object.

32 . The non-transitory CRM of claim 24 , wherein classifying the foreground object is performed on a set of subsequent frames that comprise the foreground object.

33 . A non-transitory computer readable medium comprising instructions that enable a system to:

receive a two-dimensional (2D) representation of a three-dimensional (3D) environment, wherein the 2D representation is a 2D frame of pixels encoding depth values of the 3D environment;

identify a plurality of foreground pixels in the 2D representation;

define a foreground object based on the plurality foreground pixels;

classify the foreground object; and

take an action based on the classification of the foreground object.