Sea-floor images from ROV transects during POLARSTERN cruise ANT-XVII/3 (EASIZ III) to the Weddell Sea, Antarctica

Transects of a Remotely Operated Vehicle (ROV) providing sea-bed videos and photographs were carried out during POLARSTERN expedition ANT-XVII/3 focussing on the ecology of benthic assemblages on the Antarctic shelf in the South-Eastern Weddell Sea. The ROV-system sprint 103 was equiped with two video- and one still camera, lights, flash-lights, compass, and parallel lasers providing a scale in the images, a tether-management system (TMS), a winch, and the board units. All cameras used the same main lense and could be tilted. Videos were recorded in Betacam-format and (film-)slides were made by decision of the scientific pilot. The latter were mainly made under the aspect to improve the identification of organisms depicted in the videos because the still photographs have a much higher optical resolution than the videos. In the photographs species larger than 3 mm, in the videos larger than 1 cm are recognisable and countable. Under optimum conditions the transects were strait; the speed and direction of the ROV were determined by the drift of the ship in the coastal current, since both, the ship and the ROV were used as a drifting system; the option to operate the vehicle actively was only used to avoide obstacles and to reach at best a distance of only approximately 30 cm to the sea-floor. As a consequence the width of the photographs in the foreground is approximately 50 cm. Deviations from this strategy resulted mainly from difficult ice- and weather conditions but also from high current velocity and local up-welling close to the sea-bed. The sea-bed images provide insights into the general composition of key species, higher systematic groups and ecological guilds. Within interdisciplinary approaches distributions of assemblages can be attributed to environmental conditions such as bathymetry, sediment characteristics, water masses and current regimes. The images also contain valuable information on how benthic species are associated to each other. Along the transects, small- to intermediate-scaled disturbances, e.g. by grounding icebergs were analysed and further impact to the entire benthic system by local succession of recolonisation was studied. This information can be used for models predicting the impact of climate change to benthic life in the Southern Ocean. All these approaches contribute to a better understanding of the fiunctioning of the benthic system and related components of the entire Antarctic marine ecosystem. Despite their scientific value the imaging methods meet concerns about the protection of sensitive Antarctic benthic systems since they are non-invasive and they also provide valuable material for education and outreach purposes.

Theatre Poster (subway movie poster)

General note: Title and date provided by Bettye Lane.

"Anti-Linda Lovelace" movie demonstration

General note: Title and date provided by Bettye Lane.

Anti-"Snuff" movie demonstration

General note: Title and date provided by Bettye Lane.

Anti-movie "Snuff" demonstration

General note: Title and date provided by Bettye Lane.

"Anti-Linda Lovelace" movie demonstration

General note: Title and date provided by Bettye Lane.

Men for Women's Rights at the Snuff movie demonstration

General note: Title and date provided by Bettye Lane.

Demonstration against the movie "Windows"

General note: Title and date provided by Bettye Lane.

Camera woman and sound technician at NOW conference in Houston

General note: Title and date provided by Bettye Lane.

Victor Gautbaum speaking (back to camera) at City Hall for Intro 475

General note: Title and date provided by Bettye Lane.

Bronx residents demonstrate against "Fort Apache" movie

General note: Title and date provided by Bettye Lane.

Learning and Exploiting Camera Geometry for Computer Vision

This work explores the use of statistical methods in describing and estimating camera poses, as well as the information feedback loop between camera pose and object detection. Surging development in robotics and computer vision has pushed the need for algorithms that infer, understand, and utilize information about the position and orientation of the sensor platforms when observing and/or interacting with their environment.

The first contribution of this thesis is the development of a set of statistical tools for representing and estimating the uncertainty in object poses. A distribution for representing the joint uncertainty over multiple object positions and orientations is described, called the mirrored normal-Bingham distribution. This distribution generalizes both the normal distribution in Euclidean space, and the Bingham distribution on the unit hypersphere. It is shown to inherit many of the convenient properties of these special cases: it is the maximum-entropy distribution with fixed second moment, and there is a generalized Laplace approximation whose result is the mirrored normal-Bingham distribution. This distribution and approximation method are demonstrated by deriving the analytical approximation to the wrapped-normal distribution. Further, it is shown how these tools can be used to represent the uncertainty in the result of a bundle adjustment problem.

Another application of these methods is illustrated as part of a novel camera pose estimation algorithm based on object detections. The autocalibration task is formulated as a bundle adjustment problem using prior distributions over the 3D points to enforce the objects' structure and their relationship with the scene geometry. This framework is very flexible and enables the use of off-the-shelf computational tools to solve specialized autocalibration problems. Its performance is evaluated using a pedestrian detector to provide head and foot location observations, and it proves much faster and potentially more accurate than existing methods.

Finally, the information feedback loop between object detection and camera pose estimation is closed by utilizing camera pose information to improve object detection in scenarios with significant perspective warping. Methods are presented that allow the inverse perspective mapping traditionally applied to images to be applied instead to features computed from those images. For the special case of HOG-like features, which are used by many modern object detection systems, these methods are shown to provide substantial performance benefits over unadapted detectors while achieving real-time frame rates, orders of magnitude faster than comparable image warping methods.

The statistical tools and algorithms presented here are especially promising for mobile cameras, providing the ability to autocalibrate and adapt to the camera pose in real time. In addition, these methods have wide-ranging potential applications in diverse areas of computer vision, robotics, and imaging.

Two devices, each of which measure water velocity; on the right is an acoustic device that is permanently maintained at Gumbo Limbo by PI Rene Price; on the left is a 3D camera with a long fiberoptic lens, deployed for testing purposes by collaborator Evan Variano.

http://digitalcommons.fiu.edu/fce_lter_photos/1303/thumbnail.jpg

Automatic Identification of Large Fragments in a Pile of Broken Rock Using a Time-of-Flight Camera

This paper presents a solution to part of the problem of making robotic or semi-robotic digging equipment less dependant on human supervision. A method is described for identifying rocks of a certain size that may affect digging efficiency or require special handling. The process involves three main steps. First, by using range and intensity data from a time-of-flight (TOF) camera, a feature descriptor is used to rank points and separate regions surrounding high scoring points. This allows a wide range of rocks to be recognized because features can represent a whole or just part of a rock. Second, these points are filtered to extract only points thought to belong to the large object. Finally, a check is carried out to verify that the resultant point cloud actually represents a rock. Results are presented from field testing on piles of fragmented rock. Note to Practitioners—This paper presents an algorithm to identify large boulders in a pile of broken rock as a step towards an autonomous mining dig planner. In mining, piles of broken rock can contain large fragments that may need to be specially handled. To assess rock piles for excavation, we make use of a TOF camera that does not rely on external lighting to generate a point cloud of the rock pile. We then segment large boulders from its surface by using a novel feature descriptor and distinguish between real and false boulder candidates. Preliminary field experiments show promising results with the algorithm performing nearly as well as human test subjects.

Evaluation of a ToF Camera for Remote Surveying of Underground Cavities Excavated by Jet Boring

Cigar Lake is a high-grade uranium deposit, located in northern Saskatchewan, Canada. In order to extract the uranium ore remotely, thus ensuring minimal radiation dose to workers and also to access the ore from stable ground, the Jet Boring System (JBS) was developed by Cameco Corporation. This system uses a high-powered water jet to remotely excavate cavities. Survey data is required to determine the final shape, volume, and location of the cavity for mine planning purposes and construction. This paper provides an overview of the challenges involved in remotely surveying a JBS-mined cavity and studies the potential use of a time-of-flight (ToF) camera for remote cavity surveying. It reports on data collected and analyzed from inside an experimental environment as well as on real data acquired on site from the Cigar Lake and Rabbit Lake mines.