2015
DOI: 10.1007/978-3-319-13731-5_8
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Design and Utilization of Bounding Box in Human Detection and Activity Identification

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Cited by 10 publications
(4 citation statements)
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“…The first phase predicts the next position of BB based on its previous position. The second phase updates the predicted values [28], [29]. It is important that prediction must be organized for all four parameters x c , y c , x w , and y h , which makes it possible to obtain the centroids of BB.…”
Section: B Bounding Boxmentioning
confidence: 99%
See 1 more Smart Citation
“…The first phase predicts the next position of BB based on its previous position. The second phase updates the predicted values [28], [29]. It is important that prediction must be organized for all four parameters x c , y c , x w , and y h , which makes it possible to obtain the centroids of BB.…”
Section: B Bounding Boxmentioning
confidence: 99%
“…. y s T and the matrix C N specified by (28). In can be seen that by zero coloredness matrix, n = 0, the GUFIR transforms to the standard UFIR filter [9], [24].…”
Section: ) Gufir Filtering Algorithm For Cmnmentioning
confidence: 99%
“…Figure 10 shows the template data base that were used in our work to classify human objects. Crowd was detected using a rectangular model along with central vertical line model [16]. The result is shown in figure 11.…”
Section: Fig 8 Object Detection Using Gmmmentioning
confidence: 99%
“…Prior detection of crowd was performed using object bounding rectangular model and central vertical line model. To create object bounding rectangles to each object in a frame, we have extracted some features like area, centroid, four corner points of each object and the diameter etc of an image [9]. By utilizing the coordinates of these corner points, a rectangle was drawn and from these rectangles, centre point was calculated.…”
Section: A Earlier Crowd Detection In Three Levelsmentioning
confidence: 99%