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Fishery Bulletin 108(3) 
Figure 2 
The checkerboard pattern used to calibrate and 
test the drop stereo-video camera and the still- 
frame stereo-camera systems. Images used for 
calibration were processed by using the camera 
calibration toolbox written for Matlab. An image 
taken by the still-frame stereo-camera system 
is shown with the user-selected extreme corners 
shown as white circles and the automated extrac- 
tion of all intermediate corners shown with white 
crosses. This procedure was repeated for up to 
20 different images with both systems. 
Stereo calibration required that the checkerboard 
corners be identified in the same order in each of the 
synchronous image pairs to correctly match up the 
analogous corner points. These points, once corrected 
for optical distortion in individual cameras, were used 
to compute the epipolar geometry, by iteratively solving 
for the translation and rotation vectors that describe 
the relationship between the coordinate systems of the 
two cameras (Xu and Zhang, 1996). Once these matrices 
were estimated by the software, the three-dimensional 
position of a target point viewed in both cameras could 
be determined by triangulation. 
Fish measurements with the camera 
Fish lengths were measured by using stereo triangu- 
lation functions supplied with the camera calibration 
software package (Bouguet, 2008). For the video-drop 
system, images were extracted from the two video feeds 
at 1-s intervals. The images were synchronized at the 
beginning of each transect before deployment by using 
the LED synchronization light. The images were checked 
at the end of each transect to confirm that the cameras 
remained synchronized. 
Length measurements were obtained by identifying 
the pixel coordinates of corresponding pixel locations 
in the left and right camera still frames such as a 
fish snout and tail (Fig. 3). These points were used 
to solve for the three-dimensional coordinates of the 
points in the images by triangulation, by using the 
calibration-derived parameters. Once the three-di- 
mensional coordinates of the fish snout and tail were 
obtained, the length was measured as the simple Eu- 
clidian distance between the points in real space. This 
measurement method underestimated length for fish 
whose bodies were curved; however; fish in the video 
and still camera were almost exclusively seen with 
little or no curvature in their bodies and the few indi- 
viduals that were obviously strongly curved were not 
measured. Length data were collected by using a basic 
software application built with the Matlab computing 
language (Fig. 4; available from the authors upon re- 
quest), which incorporated the triangulation function 
supplied by the calibration toolbox. 
In addition to length measurements, the three-di- 
mensional coordinates extracted from the still-frame 
images provided data on the position and orientation 
of walleye Pollock in relation to the trawl (Fig. 5). 
These data were used to determine distances of pollock 
targets to trawl components for position of fish and to 
calculate tilt and yaw for orientation of fish. 
Data collections 
Field testing of the video-drop system was conducted 
12-15 July 2008 at Zhemchug Ridges, located on 
the eastern Bering Sea shelf adjacent to Zhemchug 
Canyon where a sizable rockfish population is pres- 
ent in untrawlable and isolated rocky ridge area (Fig. 
6; Rooper et al., in press). The camera system was 
deployed off the side of the vessel FV Vesteraalen by a 
winch suspended from a block attached to the vessel’s 
crane. The camera sled drifted with the prevailing 
current, while the camera winch operator kept the 
seafloor in view and avoided any obstacles using real- 
time navigation. Stereo video was collected over 11 
transects, each ranging in length from 3.5 to 49.5 min 
and covering distances of 95 m to 1673 m. Observa- 
tions of trawl movements with the still-frame system 
were made during acoustic surveys of pollock in the 
eastern Bering Sea in June and July 2007 onboard the 
RV Oscar Dyson (Fig. 6). 
Testing of the calibrations for the two camera systems 
To test the video calibration five random still images was 
selected from the video-drop system of the checkerboard 
taken at the beginning and end of the study. Three 
intervals of 10 cm, 20 cm and 30 cm each were measured 
three times from the top to the bottom of the checker- 
board (?i = 3 for each interval) and averaged within each 
frame. The average from each frame multiplied by the 
interval combination was then tested in an analysis of 
variance to determine whether there were significant 
differences between measurements from the first and 
second measurement set. 
