R.C. Nelson and R. Polana. Qualitative recognition of motion from temporal texture. CVGIP: Image Understanding, 56:78--89, 1992. Home/Search Document Not in Database Summary Related Articles Check |
This paper is cited in the following contexts:
RSTA on the Move: Detection and Tracking of Moving Objects from an .. - Davis (1996) (2 citations) (Correct)
....mainly due to regions that do not fit the 2D motion assumption, since they are also segmented after the difference image is thresholded. Temporal median filters combined with velocity tuned filters are used in [9] to detect independently moving objects (IMOs) Qualitative approaches [10, 11] to the detection of IMOs could also benefit from electronic image stabilization. During these tests the system was set to use search windows and SSD windows of the same size (7 Theta 7) For these settings, the system is able to process about 20 frames per second. Table 1 shows how the frame ....
....based on temporal texture analysis, where we extract statistical spatial and temporal features from approximations to the motion field and use techniques analogous to those developed for gray scale texture analysis to classify regional activities. Some results in this area are described in [11]. In a second approach, which we term activity recognition, we use the spatial and temporal arrangement of motion features in conjunction with simple geometric image analysis to identify complexly moving objects such as machinery and locomoting people and animals [14] The remainder of this ....
R.C. Nelson and R. Polana. Qualitative recognition of motion from temporal texture. CVGIP: Image Understanding, 56:78--89, 1992.
Recognizing People by Their Gait: The Shape of Motion - Little, Boyd (1996) (44 citations) (Correct)
....by the inverse of the variance in that dimension) 24] but the Euclidean works better. With this little data the variance estimates are unreliable. 5 Discussion 5. 1 Comparison with Other Methods The other techniques for representing human motion have been applied to recognizing activities [26], but only Niyogi and Adelson [27] have specifically tried to recognize individuals by their motion. Our imaging situation is exactly the same they used to achieve a recognition rate of up to 83 . There is no reason to expect that their method would not work well with this data. Niyogi and ....
Nelson, R. C. and Polana, R. Qualitative recognition of motion from temporal texture. Journal of Visual Communication and Image Representation, 5:172--180, 1994.
RSTA on the Move: Detection and Tracking of Moving Objects.. - Davis, Bajcsy, al. (1996) (2 citations) (Correct)
....based on temporal texture analysis, where we extract statistical spatial and temporal features from approximations to the motion field and use techniques analogous to those developed for grayscale texture analysis to classify regional activities. Some results in this area are described in [ Nelson and Polana, 1992 ] In a second approach, which we term activity recognition, we use the spatial and temporal arrangement of motion features in conjunction with simple geometric image analysis to identify complexly moving objects such as machinery and locomoting people and animals [ Polana and Nelson, 1993 ] ....
R.C. Nelson and R. Polana. Qualitative recognition of motion from temporal texture. CVGIP: Image Understanding, 56:78--89, 1992.
Recognizing People by Their Gait: The Shape of Motion - Little, Boyd (1996) (44 citations) (Correct)
....on recovering the boundaries of moving figures in the xt domain [NA94a] and recently [NA94b] xyt spatiotemporal solids, followed by fitting deformable splines to the contours. These splines are the elements of the articulated nonrigid model whose features aid recognition. Polana and Nelson[PN93, NP94] characterize the temporal texture of a moving figure by summing the energy of the highest amplitude frequency and its multiples . They use Fourier analysis. The results are normalized with respect to total energy so that the measure is 1 for periodic events and 0 for a flat spectrum. Their ....
....by the inverse of the variance in that dimension) Mah36] but the Euclidean works better. With this little data the variance estimates are unreliable. 5 Discussion 5. 1 Comparison with Other Methods The other techniques for representing human motion have been applied to recognizing activities[NP94] but only Niyogi and Adelson[NA94a] have specifically tried to recognize individuals by their motion. Our imaging situation is exactly the same they used to achieve up to 83 recognition rate. There is no reason to expect that their method would not work well with this data. They acquire ....
Randall C. Nelson and Ramprasad Polana. Qualitative recognition of motion from temporal texture. Journal of Visual Communication and Image Representation, 5:172--180, 1994.
RSTA on the Move: Detection and Tracking of Moving Objects from .. - Larry Davis (1996) (2 citations) Self-citation (Nelson) (Correct)
....based on temporal texture analysis, where we extract statistical spatial and temporal features from approximations to the motion field and use techniques analogous to those developed for grayscale texture analysis to classify regional activities. Some results in this area are described in [ Nelson and Polana, 1992 ] In a second approach, which we term activity recognition, we use the spatial and temporal arrangement of motion features in conjunction with simple geometric image analysis to identify complexly moving objects such as machinery and locomoting people and animals [ Polana and Nelson, 1993 ] ....
R.C. Nelson and R. Polana. Qualitative recognition of motion from temporal texture. CVGIP: Image Understanding, 56:78--89, 1992.
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