1. A compound of formula (I)
wherein:
X1 and X2 are selected from the group consisting of O, N and S;
n is 0 and m is 1, 2 or 3, or n is 1 and m is 0, 1 or 2;
R1 and R4 are independently selected from the group consisting of
(1) -Q-Ra,
(2) hydroxyl,
(3) a carbocyclic group having from 3 to 8 ring carbon atoms, optionally having from one to three ring carbon atoms replaced with S, N, C(\u2550O) or O,
(4) \u2014C6-10 aryl, and
(5) a heteroaryl group having from 5-10 ring atoms,
wherein said carbocyclic group, aryl and heteroaryl are unsubstituted or substituted with one or more
(a) halogen,
(b) cyano,
(c) \u2014NO2,
(d) \u2014C1-6 alkyl, wherein said alkyl is unsubstituted or substituted with one or more halogen,
(e) \u2014C1-6 alkoxy,
(f) \u2014C(\u2550O)\u2014(O)z\u2014Rb,
(g) \u2014C(\u2550O)\u2014NRbRb\u2032,
(h) \u2014O\u2014C(\u2550O)\u2014Rb,
(i) \u2014S(O)yRb,
(j) \u2014S(O)yNRbRb\u2032,
(k) \u2014S(O)yNRb\u2014C(\u2550O)\u2014C1-6 alkyl, wherein said alkyl is unsubstituted or substituted with one or more halogen,
(l) \u2014NRbRb\u2032,
(m) \u2014NRb\u2014C(\u2550O)\u2014Rb\u2032, and
y is 0, 1 or 2
z is 0 or 1;
Q is selected from the group consisting of
(a) \u2014O\u2014,
(b) \u2014O\u2014C(\u2550O)\u2014,
(c) \u2014S\u2014,
(d) \u2014SO2\u2014,
(e) \u2014NRb,
(f) \u2014NRb\u2014C(\u2550O)\u2014, and
(g) \u2014O\u2014PO3\u2014;
Ra, Rb and Rb\u2032 are independently selected from the group consisting of:
(i) \u2014C1-10 alkyl,
(ii) \u2014C2-10 alkenyl,
(iii) \u2014C2-10 alkynyl,
(iv) a carbocyclic group having from 3 to 8 ring carbon atoms, optionally having from one to three ring carbon atoms replaced with S, N, C(\u2550O) or O, and
(v) \u2014C6-10 aryl,
wherein said carbocyclic group, alkyl, alkenyl, alkynyl and aryl are unsubstituted or substituted with one or more
\u2003(A) halogen,
\u2003(B) cyano,
\u2003(C) \u2014NO2,
\u2003(D) \u2014C1-6 alkyl, wherein said alkyl is unsubstituted or substituted with one or more halogen,
\u2003(E) \u2014C1-6alkoxy,
\u2003(F) \u2014C(\u2550O)\u2014(O)z\u2014Rc,
\u2003(G) \u2014C(\u2550O)\u2014NRcRc\u2032,
\u2003(H) \u2014O\u2014C(\u2550O)Rc,
\u2003(I) \u2014S(O)yRc,
\u2003(J) \u2014S(O)yNRcRc\u2032,
\u2003(K) \u2014S(O)yNR\u2014c(\u2550O)\u2014C1-6 alkyl, wherein said alkyl is unsubstituted or substituted with one or more halogen,
\u2003(L) \u2014NRcRc\u2032, and
\u2003(M) \u2014NRc\u2014C(\u2550O)Rc\u2032,
\u2003and Rc and Rc\u2032 are independently selected from the group consisting of
\u2003(1) hydrogen,
\u2003(2) \u2014C1-10 alkyl,
\u2003(3) \u2014C2-10 alkenyl,
\u2003(4) \u2014C2-10 alkynyl,
\u2003(5) a carbocyclic group having from 3 to 8 ring carbon atoms, optionally having from one to three ring carbon atoms replaced with S, N, C(\u2550O) or O,
\u2003(6) \u2014C6-10 alkyl-C6-10 aryl, and
\u2003(7) a heteroaryl group having from 5-10 ring atoms;
R2, R3, R5 and R6 are independently selected from the group consisting of
(1) hydrogen,
(2) -Cl -l0 alkyl,
(3) -C2-10 alkenyl,
(4) C2-10 alkynyl, or
(5) <6-10 aryl,
wherein said alkyl, alkenyl, alkynyl, and aryl are unsubstituted or substituted with one or more
(a) halogen,
(b) cyano,
(c) \u2014NO2,
(d) \u2014C1-6 alkyl, wherein said alkyl is unsubstituted or substituted with one or more halogen,
(e) \u2014C1-6 alkoxy,
(f) \u2014C(\u2550O)\u2014(O)z\u2014Re,
(g) \u2014C(\u2550O)\u2014NReRe\u2032,
(h) \u2014O\u2014C(\u2550O)\u2014Re,
(i) \u2014S(O)yRe,
(j) \u2014S(O)y\u2014NReRe\u2032,
(k) \u2014S(O)y\u2014NRe\u2014C(\u2550O)\u2014C1-6 alkyl, wherein said alkyl is unsubstituted or substituted with one or more halogen,
(l) \u2014NReRe\u2032, and
(m) \u2014NRe\u2014C(\u2550O)Re,
and Re and Re\u2032 are independently selected from the group consisting of
(i) hydrogen,
(ii) \u2014C1-10 alkyl,
(iii) \u2014C2-10 alkenyl,
(iv) \u2014C2-10 alkynyl,
(v) a carbocyclic group having from 3 to 8 ring carbon atoms, optionally having from one to three ring carbon atoms replaced with S, N, C(\u2550O) or O,
(vi) \u2014C0-10 alkyl-C6-10 aryl, and
(vii) a heteroaryl group having from 5-10 ring atoms;
or R5 is hydrogen and R4 and R6 are linked together to form a carbocyclic group having from 3 to 8 ring carbon atoms, optionally having a single carbon-carbon double bond, and optionally having from one to three ring carbon atoms replaced with S, N, C(\u2550O) or O,
said carbocyclic group unsubstituted or substituted with one or more
(a) hydroxyl,
(b) \u2014NRfRf\u2032,
(c) \u2014C(\u2550O)\u2014O\u2014Rf,
(d) \u2014OPO3,
wherein Rf is selected from the group consisting of
(i) hydrogen, and
(ii) \u2014C1-6 alkyl,
and pharmaceutically acceptable salts thereof.
2. The compound of claim 1 wherein X1 and X2 are both \u2014O\u2014.
3. The compound of claim 1 wherein X1 is \u2014O\u2014 and X2 is \u2014NH\u2014, or X1 is \u2014NH\u2014 and X2 is \u2014O\u2014.
4. The compound of claim 1, wherein n is 0 and m is 1.
5. The compound of claim 1, wherein R5 and R6 are each hydrogen, and R4 is -Q-Ra.
6. The compound of claim 1 which is
wherein R4 is as defined in claim 1, and pharmaceutically acceptable salts thereof.
7. A method of treating stroke, comprising administering a compound of claim 1 to a patient in need thereof.
8. The method of claim 7, wherein the patient is an acute stroke patient.
9. A compound of formula (II):
wherein Z is an amino acid or amino acid derivative which is linked to (II) at a nitrogen atom via an imine bond, and pharmaceutically acceptable salts thereof.
10. The compound of claim 9 wherein Z is an amino acid selected from the group consisting of glycine, alanine, arginine, asparagine, aspartic acid, glutamic acid, cystine, glutamine, histidine, leucine, isoleucine, lysine, methionine, phenylalanine, proline, serine, threonine, tryptophan, tyrosine or valine.
11. A method of treating stroke, comprising administering a compound of claim 6 to a patient in need thereof.
12. The method of claim 11, wherein the patient is an acute stroke patient.
13. A compound of formula (III):
wherein R7 is a sugar molecule which is fused compound (III), and v is 1 or 2.
14. A method of treating stroke, comprising administering a compound of claim 13 to a patient in need thereof.
15. The method of claim 14, wherein the patient is an acute stroke patient.
16. A method of treating stroke, comprising administering a compound of claim 16 to a patient in need thereof.
17. A pharmaceutical composition suitable for intravenous administration, comprising a compound of claim 1, and a pharmaceutically acceptable carrier.
18. A pharmaceutical composition suitable for intravenous administration, comprising a compound of claim 9, and a pharmaceutically acceptable carrier.
19. A pharmaceutical composition suitable for intravenous administration, comprising a compound of claim 13 and a pharmaceutically acceptable carrier.
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. A system for object cueing in motion imagery, the system comprising:
one or more processors and a non-transitory memory having instructions encoded thereon such that when the instructions are executed, the one or more processors perform operations of:
extracting key points and bio-inspired features from input motion imagery, wherein the input motion imagery comprises a sequence of image frames obtained with a sensor;
comparing bio-inspired features between consecutive image frames in the sequence of image frames to identify a set of image frames having similar bio-inspired features;
matching keypoints between the set of image frames to generate a candidate set of matching keypoints;
determining a ground plane homography model that fits the candidate set of matching keypoints to generate a set of correct matching keypoints and an accurate homography transformation between the set of image frames;
registering each image within a selected time window into a reference frame’s coordinate system using the homography transformation;
obtaining a difference image between the reference frame and each registered image frame within the time window, resulting in a plurality of difference images;
accumulating the plurality of difference images to calculate a detection image;
detecting salient regions from the detection image by blob extraction; and
producing object cues for surveillance use based on the detected salient regions.
2. The system as set forth in claim 1, wherein the one or more processors further perform an operation of thresholding the detection image by a predefined threshold value.
3. The system as set forth in claim 2, wherein the one or more processors further perform an operation of automatically selecting parameters for object cueing based on information obtained from the sensor, wherein the parameters comprise at least one of: time window size, minimum pixel area of a target of interest, maximum pixel area of a target of interest, and the predefined threshold value.
4. The system as set forth in claim 3, wherein the one or more processors further perform an operation of determining a size of a time window using information obtained from the sensor according to the following:
k
=
(
half
length
)
(
target
speed
)
*
(
fps
)
,
where k denotes a half size of a time window, halflength denotes half of the length of a target, targetspeed denotes the speed of the target, and fps denotes a video frame rate in frames per second.
5. The system as set forth in claim 4, wherein the one or more processors further perform an operation of calculating the detection image according to the following:
D=Th{\u03a3i=02kabs(Fi\u2212Fk)} th=k*m*\u03c3,
where D denotes the detection image, \u03a3 denotes a summation, abs denotes absolute value, Fi is the ith image frame within a time window of size 2k+1, Fk is a current image frame, Th represents a thresholding function, th denotes the predefined threshold value, \u03c3 is an average background noise level, and m is a scaler for \u03c3.
6. The system as set forth in claim 1, wherein the one or more processors further perform an operation of using random sample consensus to determine the ground plane homography model.
7. A computer-implemented method for object cueing in motion imagery, comprising:
an act of causing a data processor to execute instructions stored on a non-transitory memory such that upon execution, the data processor performs operations of:
extracting key points and bio-inspired features from input motion imagery, wherein the input motion imagery comprises a sequence of image frames obtained with a sensor;
comparing bio-inspired features between consecutive image frames in the sequence of image frames to identify a set of image frames having similar bio-inspired features;
matching keypoints between the set of image frames to generate a candidate set of matching keypoints;
determining a ground plane homography model that fits the candidate set of matching keypoints to generate a set of correct matching keypoints and an accurate homography transformation between the set of image frames;
registering each image frame within a selected time window into a reference frame’s coordinate system using the homography transformation;
obtaining a difference image between the reference frame and each registered image frame within the time window, resulting in a plurality of difference images;
accumulating the plurality of difference images to calculate a detection image;
detecting salient regions from the detection image by blob extraction; and
producing object cues for surveillance use based on the detected salient regions.
8. The method as set forth in claim 7, wherein the data processor further performs an operation of thresholding the detection image by a predefined threshold value.
9. The method as set forth in claim 8, wherein the data processor further performs an operation of automatically selecting parameters for object cueing based on information obtained from the sensor, wherein the parameters comprise at least one of: time window size, minimum pixel area of a target of interest, maximum pixel area of a target of interest, and the predefined threshold value.
10. The method as set forth in claim 9, wherein the data processor further performs an operation of determining a size of a time window using information obtained from the sensor according to the following:
k
=
(
half
length
)
(
target
speed
)
*
(
fps
)
,
where k denotes a half size of a time window, halflength denotes half of the length of a target, targetspeed denotes the speed of the target, and fps denotes a video frame rate in frames per second.
11. The method as set forth in claim 10, wherein the data processor further performs an operation of calculating the detection image according to the following:
D=Th{\u03a3i=02kabs(Fi\u2212Fk)} th=k*m*\u03c3,
where D denotes the detection image, \u03a3 denotes a summation, abs denotes absolute value, Fi is the ith image frame within a time window of size 2k+1, Fk is a current image frame, Th represents a thresholding function, th denotes the predefined threshold value, \u03c3 is an average background noise level, and m is a scaler for \u03c3.
12. The method as set forth in claim 7, wherein the data processor further performs an operation of using random sample consensus to determine the ground plane homography model.
13. A computer program product for object cueing in motion imagery, the computer program product comprising computer-readable instructions stored on a non-transitory computer-readable medium that are executable by a computer having a processor for causing the processor to perform operations of:
extracting key points and bio-inspired features from input motion imagery, wherein the input motion imagery comprises a sequence of image frames obtained with a sensor;
comparing bio-inspired features between consecutive image frames in the sequence of image frames to identify a set of image frames having similar bio-inspired features;
matching keypoints between the set of image frames to generate a candidate set of matching keypoints;
determining a ground plane homography model that fits the candidate set of matching keypoints to generate a set of correct matching keypoints and an accurate homography transformation between the set of image frames;
registering each image frame within a selected time window into a reference frame’s coordinate system using the homography transformation;
obtaining a difference image between the reference frame and each registered image frame within the time window, resulting in a plurality of difference images;
accumulating the plurality of difference images to calculate a detection image;
detecting salient regions from the detection image by blob extraction; and
producing object cues for surveillance use based on the detected salient regions.
14. The computer program product as set forth in claim 13, further comprising instructions for causing the processor to perform an operation of thresholding the detection image by a predefined threshold value.
15. The computer program product as set forth in claim 14, further comprising instructions for causing the processor to perform an operation of automatically selecting parameters for object cueing based on information obtained from the sensor, wherein the parameters comprise at least one of: time window size, minimum pixel area of a target of interest, maximum pixel area of a target of interest, and the predefined threshold value.
16. The computer program product as set forth in claim 15, further comprising instructions for causing the processor to perform an operation of determining a size of a time window using information obtained from the sensor according to the following:
k
=
(
half
length
)
(
target
speed
)
*
(
fps
)
,
where k denotes a half size of a time window, halflength denotes half of the length of a target, targetspeed denotes the speed of the target, and fps denotes a video frame rate in frames per second.
17. The computer program product as set forth in claim 16, further comprising instructions for causing the processor to perform an operation of calculating the detection image according to the following:
D=Th{\u03a3i=02kabs(Fi\u2212Fk)} th=k*m*\u03c3,
where D denotes the detection image, \u03a3 denotes a summation, abs denotes absolute value, Fi is the ith image frame within a time window of size 2k+1, Fk is a current image frame, Th represents a thresholding function, th denotes the predefined threshold value, \u03c3 is an average background noise level, and m is a scaler for \u03c3.
18. The computer program product as set forth in claim 13, further comprising instructions for causing the processor to perform an operation of using random sample consensus to determine the ground plane homography model.