ALERT VOLUME NORMALIZATION IN A VIDEO SURVEILLANCE SYSTEM
Techniques are disclosed for normalizing and publishing alerts using a behavioral recognition-based video surveillance system configured with an alert normalization module. Certain embodiments allow a user of the behavioral recognition system to provide the normalization module with a set of relative weights for alert types and a maximum publication value. Using these values, the normalization module evaluates an alert and determines whether its rareness value exceed a threshold. Upon determining that the alert exceeds the threshold, the module normalizes and publishes the alert.
1 . A method for normalizing and publishing an alert generated by a behavioral recognition system, the method comprising:
receiving an alert having a type and an original rareness value,
converting the original rareness value to an alert percentile value,
upon determining that the alert percentile value is greater than a percentile threshold, normalizing the alert, and
publishing the alert.
2 . The method of claim 1 , wherein the percentile threshold is
ξ
i
=
1
-
v
i
N
i
,
where v i is a maximum allowed alert counts for the alert type value and N i is an estimated next-day alert counts value.
3 . The method of claim 2 , wherein the percentile threshold is
ξ
i
=
N
i
+
p
i
-
(
1
+
λ
)
v
i
N
i
if
p
i
>
v
i
,
where p i is a number of published alerts for a current day and λ is an overage value.
4 . The method of claim 1 , wherein normalizing the alert further comprises calculating a normalized rareness value
η
i
=
ɛ
i
-
ξ
i
1
-
ξ
i
,
where ε i is the alert percentile value and ξ i is the percentile threshold.
5 . The method of claim 4 , wherein the normalized rareness value is
η
i
=
1
-
rand
m
+
∑
k
=
1
B
m
k
p
+
∑
k
=
1
B
p
k
if
r
=
1
,
where m is a current number of alerts having an original rareness value being 1 for a current day, p is a current number of published alerts for a current day, and r is the original rareness value.
6 . The method of claim 1 , wherein publishing the alert further comprises calculating a publication rank value β=min(P,N p )*(1−η i ), where P is a maximum publication value, N p is a rank-renormalization constant, and η i is a normalization rareness value.
7 . The method of claim 6 , further comprising upon determining that the publication rank value is less than a maximum dispatch value, dispatching the alert.
8 . A computer-readable storage medium storing instructions, which, when executed on a processor, performs an operation for normalizing and publishing an alert generated by a behavioral recognition system, the method comprising, the operation comprising:
receiving an alert having a type and an original rareness value,
converting the original rareness value to an alert percentile value,
upon determining that the alert percentile value is greater than a percentile threshold, normalizing the alert, and
publishing the alert.
9 . The computer-readable storage medium of claim 8 , wherein the percentile threshold is
ξ
i
=
1
-
v
i
N
i
,
where v i is a maximum allowed alert counts for the alert type value and N i is an estimated next-day alert counts value.
10 . The computer-readable storage medium of claim 9 , wherein the percentile threshold is
ξ
i
=
N
i
+
p
i
-
(
1
+
λ
)
v
i
N
i
if
p
i
>
v
i
,
where p i is a number of published alerts for a current day and λ is an overage value.
11 . The computer-readable storage medium of claim 8 , wherein normalizing the alert further comprises calculating a normalized rareness value
η
i
=
ɛ
i
-
ξ
i
1
-
ξ
i
,
where ε i is the alert percentile value and ξ i is the percentile threshold.
12 . The computer-readable storage medium of claim 11 , wherein the normalized rareness value is
η
i
=
1
-
rand
m
+
∑
k
=
1
B
m
k
p
+
∑
k
=
1
B
p
k
if
r
=
1
,
where m is a current number of alerts having an original rareness value being 1 for a current day, p is a current number of published alerts for a current day, and r is the original rareness value.
13 . The computer-readable storage medium of claim 8 , wherein publishing the alert further comprises calculating a publication rank value β=min(P,N p )*(1−η i ), where P is a maximum publication value, N p is a rank-renormalization constant, and η i is a normalization rareness value.
14 . The computer-readable storage medium of claim 13 , further comprising upon determining that the publication rank value is less than a maximum dispatch value, dispatching the alert.
15 . A system comprising:
a processor and
a memory for hosting an application, which, when executed on the processor, performs an operation for normalizing and publishing an alert generated by a behavioral recognition system, the operation comprising:
receiving an alert having a type and an original rareness value,
converting the original rareness value to an alert percentile value,
upon determining that the alert percentile value is greater than a percentile threshold, normalizing the alert, and
publishing the alert.
16 . The system of claim 15 , wherein the percentile threshold is
ξ
i
=
1
-
v
i
N
i
,
where v i is a maximum allowed alert counts for the alert type value and N i is an estimated next-day alert counts value.
17 . The system of claim 16 , wherein the percentile threshold is
ξ
i
=
N
i
+
p
i
-
(
1
+
λ
)
v
i
N
i
if
p
i
>
v
i
,
where p i is a number of published alerts for a current day and λ is an overage value.
18 . The system of claim 15 , wherein normalizing the alert further comprises calculating a normalized rareness value
η
i
=
ɛ
i
-
ξ
i
1
-
ξ
i
,
where ε i is the alert percentile value and ξ i is the percentile threshold.
19 . The system of claim 18 , wherein the normalized rareness value is
η
i
=
1
-
rand
m
+
∑
k
=
1
B
m
k
p
+
∑
k
=
1
B
p
k
if
r
=
1
,
where m is a current number of alerts having an original rareness value being 1 for a current day, p is a current number of published alerts for a current day, and r is the original rareness value.
20 . The system of claim 15 , wherein publishing the alert further comprises calculating a publication rank value β=min(P,N p )*(1−η i ), where P is a maximum publication value, N p is a rank-renormalization constant, and η i is a normalization rareness value.
21 . The system of claim 20 , further comprising upon determining that the publication rank value is less than a maximum dispatch value, dispatching the alert.