1. A method of generating and applying a set of policy rules for enforcement by a policy enforcement function at a node of a communication network, said node routing packet flows to and from users of the network, the method comprising:
at a service level control function, determining source and destination addressing information for a packet flow to be transported through said node;
sending said determined addressing information to a policy rules generating function, the policy rules generating function maintaining or having access to service and mobility policies for users of the communication network;
at the policy rules generating function, generating said set of policy rules on the basis of the source and destination addressing information and the appropriate service and mobility policies, the rules specifying a route optimization policy; and
sending the generated set of policy rules to the policy enforcement function; and
applying the set of policy rules to traffic flows to determine whether or not route optimization is allowed.
2. The method according to claim 1, wherein said service policy is a policy which takes no account of mobility.
3. The method according to claim 1, wherein said mobility policy defines access rights to Mobile IP for a plurality of users.
4. The method according to claim 1, wherein said mobility policy specifies for a user, Correspondent Nodes with which the user is permitted to employ route optimization.
5. The method according to claim 1, wherein said mobility policy specifies Home Agents via which a user is permitted to route Mobile IP traffic.
6. The method according to claim 1, wherein said mobility policy specifies packet types which are permitted to be used with Mobile IP.
7. The method according to claim 1, wherein said service level control function is located within a node of an IP Multimedia Subsystem, and the policy enforcement function is located with a GGSN of a cellular telephone network.
8. The method according to claim 1, wherein said source and destination addressing information provided by the service level control function comprises at least the source and destination addresses of the packet flow.
9. The method according to claim 8, wherein said addressing information also comprises the source and destination port numbers.
10. The method according to claim 1, further comprising sending from the service level control function to the policy rules generating function, an identification of a transport protocol utilized for the traffic flow, the policy rules generating function using knowledge of the transport protocol to generate the policy rules.
11. The method according to claim 1, wherein the policy rules generating function comprises a first part for applying said service policies to the received addressing information to generate a set of service rules, and a second part for applying the mobility policy to the service rules to generate said set of policy rules.
12. The method according to claim 11, wherein said second part extends the service rules to take into account Mobile IP addressing formats.
13. The method according to claim 12, wherein said service rules include source and destination address information for the IP flow, while each policy rule includes the home and care-of-address of the user for whom a policy is being applied, Correspondent Node home and care-of-addresses or address ranges, and an action for packets matching these address conditions.
14. The method according to claim 1, wherein a policy rule specifies allowed or disallowed Home Agent addresses and packet types.
15. The method according to claim 1, wherein a policy rule comprises includes the following fields:
Mobile Node home address;
Mobile Node care-of-address;
Home Agent address (or address range);
Correspondent Node home address;
Correspondent Node care-of-address;
Packet category identifying whether or not Mobile IP applies to a packet and if so, in what manner Mobile IP applies;
Transport protocol;
Mobile Node side port number; and
Correspondent Node side port number.
16. The method according to claim 1, wherein a policy rule includes a priority value which identifies to the policy enforcement function the priorities with which the policy rules are to be applied.
17. A node for use within a communication network, the node comprising:
means for receiving from a service level control function, addressing information relating to a packet flow through the network;
policy rules generating means having access to service and mobility policies for users of the communication network, and being arranged to generate a set of policy rules based on source and destination addressing information and the appropriate service and mobility policies, the rules specifying a route optimization policy; and
means for sending the generated set of policy rules to a policy enforcement function within the communication network.
The claims below are in addition to those above.
All refrences to claim(s) which appear below refer to the numbering after this setence.
1. An apparatus for detecting an upper body, comprising:
an omega field detecting unit configured to detect an omega field including a shape formed of a face and a shoulder line of a human from a target image, the omega field detecting unit including:
a resizing unit configured to reduce a width or a length of the target image by a predetermined percentage;
a first feature deducing unit configured to deduce a weight of coordinates of the reduced target image and deduce a first feature on the basis of the deduced weight; and
an omega field judging unit configured to judge whether the omega field is included in the target image by comparing the first feature with a reference value;
a face detecting unit configured to detect whether the human face is included in the omega field;
a siderear verifying unit configured to verify whether a side or a rear of a human exists in the omega field if the human face is not detected by the face detecting unit; and
an upper body judging unit configured to judge whether the upper body of a human is included in the target image on the basis of a result of detecting the human face and configured to judge whether the upper body of a human is included in the target image on the basis of a result of verifying whether a side or a rear of a human exists in the omega field.
2. The apparatus of claim 1, wherein the omega field detecting unit further includes:
a first memory configured to store a three-dimensional first lookup table that is trained based.
3. The apparatus of claim 2, wherein the first lookup table is trained and deduced based on the adaboost algorithm using an omega shape example image as a positive set and the other images than the omega shape example image as a negative set.
4. The apparatus of claim 1, wherein the siderear verifying unit includes:
a second memory configured to store a three-dimensional second lookup table trained based on the adaboost algorithm;
a second feature deducing unit configured to deduce a weight of coordinates of the omega field based on the second lookup table and deduce a second feature based on the deduced weight; and
a siderear judging unit configured to judge whether the side or the rear of a human is included in the omega field by comparing the second feature with a reference value.
5. The apparatus of claim 4, wherein the second lookup table is trained and deduced based on the adaboost algorithm using a human siderear example image as a positive set and the other images than the human siderear example image as a negative set.
6. A method for detecting an upper body, comprising:
detecting an omega candidate area including a shape formed of a face and a shoulder line of a human from a target image;
cutting the target image into the upper body candidate area including the omega candidate area;
detecting whether a human face appears in the upper body candidate area;
detecting whether a side or a rear of a human appears in the upper body candidate area if the human face is not detected in the upper body candidate area, and
judging whether the upper body of the human is included in the target image according to a result of detecting the human face and according to a result of detecting wherein the omega candidate area is detected by:
reducing a width or a length of the target image by a predetermined percentage,
deducing a weight of coordinates of the reduced target image and deducing a first feature on the basis of the deduced weight, and
judging whether the omega field is included in the target image by comparing the first feature with a reference value.
7. The method of claim 6, wherein the judging includes:
if the human face is detected in the detecting of the human face, judging that the human upper body is included in the target image.
8. The method of claim 6, wherein the detecting includes:
determining whether a width or a length of the target image is larger than a predetermined threshold TH;
reducing the size of the target image by a predetermined percentage if the width or the length of the target image is larger than the predetermined threshold;
pre-processing the resized target image;
deducing a first feature from the pre-processed target image; and
judging if the omega candidate area is included in the target image based on the deduced first feature.
9. The method of claim 6, wherein the detecting of the side or the rear of a human includes:
pre-processing the upper body candidate area, the pre-processing including any one of an edge detecting process and an MCT process;
deducing a second feature from the pre-processed upper body candidate area; and
judging whether the side or the rear of a human exists in the upper body candidate area by comparing the second feature with a predetermined reference value.