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Navneet dalal phd thesis

navneet dalal phd thesis

negative training or test images). This has been done to avoid boundary conditions (thus to avoid any particular bias in the classifier). Window stride (sampling distance between two consecutive windows) at any scale is 8 pixels. Normalized Images, folders 'train_64x128_H96' and 'test_64x128_H96' correspond to normalized dataset as used in above referenced paper. New image width and height are calculated using the formulas: NewWidthfloor(OrigWidth/Scale) and Here scale1 implies the original image size. Also while testing negative images, to create negative windows, we use the same sampling structure. Contributions, the data set contains images from several different sources: Images from, gRAZ 01 dataset, though annotation files are completely new. The method is then re-trained using this augmented set (initial 12180 hard examples) to produce the final detector. Disclaimer, tHIS data SET IS provided "AS IS" AND without ANY express OR implied warranties, including, without limitation, THE implied warranties OF merchantability AND fitness foarticular purpose.

This dataset was collected as part of research work on detection of upright people in images and video. The research is described in detail in cvpr 2005 paper. Annotations may not be right; in particular at times portions of annotated bounding boxes may be outside or inside the object. We shift all windows by (floor(MarginX/2 floor(MarginY/2). Note, only upright persons (with person height 100) are marked in each image. For example, if image size at current level is (75,130 margin (with stride of 8 and window size of 64,128) left is (3,2). Starting scale in scale-space pyramid above is one and we keep adding one more level in the pyramid till floor(ImageWidth/Scale) 64 and Scale ratio between two consecutive levels in the pyramid.2.

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Few of images are taken from the web using google images. For any questions, comments or other issues please contact. The images provided above may have certain copyright issues. All examples with score greater than zero are considered hard examples. You may download the whole data set from here (970MB). Folders 'Train' and 'Test' correspond, respectively, to original training and test images.