Sample Images for CS 664 - Computer Vision
Prof. Dan Huttenlocher
Fall 2003

Images for Assignment 2

These are the test images for Assignment 2, the image motion tracker.

• Test image pairs for part 1: Downloaded zip of ppm files

  There are 8 pairs of images, each named xxxx_1.ppm and xxxx_2.ppm. Please run your implementation of part #1 on all 8 pairs, and include the output (motion vector estimate) for each pair in your report.

  (Hint: The ideal motion vector between boxes_1.ppm and boxes_2.ppm is a 0.5 pixel shift to the left. The ideal motion vector between moreboxes_1.ppm and moreboxes_2.ppm is a 0.5 pixel upward shift.)

• Test image pairs for part 2: Download zip of ppm files (updated 10/23/03 - see note below)

  There are 4 pairs of images, again named xxxx_1.ppm and xxxx_2.ppm.

  10/23/03 Note: Don't worry if your algorithm doesn't work well on cayuga_1.ppm and cayuga_2.ppm. I included them in the zip file by mistake. I've included an additional pair (mcfaddin_1 and mcfaddin_2) as a substitute.

  Important note: Contrary to the information on the assignment sheet, some of these images require using a Gaussian Pyramid with more than 5 levels. You may want to make the number of levels in the Gaussian Pyramid a parameter of your algorithm. I (David) found that 10 levels worked well for all images.

  (Hint: Start with start_1.ppm and start_2.ppm, because they have the least amount of motion and no distortion.)

• Test image pairs for part 3: Download zip of ppm files

• Test image pairs for part 4: Use a few pairs (of your choice) from the part 2 and part 3 image sets.

Images for Assignment 1

Below you'll find images to use as test data for assignment 1, the stop sign detector. We recommend that you start with image set #1, which contains relatively easy images (i.e. the signs are prominent, parallel to the image plane of the camera, roughly uniform in size and orientation, etc.). We'll add another image set later that will be a little more challenging. Feel free to use your own images for testing as well.

All images are in .PPM format. The libraries recommended on the course web site support reading and writing .ppm files. The .ppm format is simple enough that you can also write your own I/O routines instead, if you wish. The cost of this simplicity is that .ppm files do not support compression and hence can be very large.

Note that a few of the test images do not contain stop signs. Running your algorithm on these images may help you identify potential false alarms (e.g. other objects that are incorrectly identified as stop signs by your program) and revise your object model accordingly.

• Image set #1: Download zip archive of .ppm files (~30 MB) or view thumbnails.
  Note: The above archive of ppm files is very large. Alternatively, you can download a zip archive of the images in .jpg format (~2 MB), but you will have to convert the .jpg files to .ppm files on your local machine.

• Sample output for image set #1
  These are sample output images generated by running a subset of image set #1 through David's (TA's) implementation of assignment #1. Of course, these results are just samples; your detector will undoubtedly produce different outputs due to different model parameters, etc.

• Image set #2: Download zip archive of .ppm files (~30 MB) or view thumbnails.
  Image set #2 contains a few more difficult images to test the robustness of your model. Note that some of these images are synthetic, but hopefully they will still be useful for evaluating the strengths and weaknesses of your detector.