Browsing by Author "Godin, Theresa"

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    Timelapse Image Analysis Manual
    (2012-08-17T15:35:53Z) Greenberg, Saul; Godin, Theresa
    Using a timelapse camera, scientists can track entities (such as people and wildlife) and conditions (such as weather and visibility) that occur in a particular place over time. Cameras are placed at strategic locations, where images are automatically taken at regular intervals (e.g., every 5 minutes, every hour), or via motion detection. After collecting the camera's card, an analyst visually examines each image and counts/describes the entities and conditions of interest. The Timelapse Image Analyser described in this manual helps scientists do this last visual analysis and counting step. In brief, the tool lets a coordinating biologist configure a series of 'codes' specific to the biologist's project and to the sets of images that require analysis. An analyzer later opens an image set using the tool. As a first step, the tool automatically: goes through all images and extracts information it can such as dates and times; and categorizes unusual images including dark ones (night time) and corrupted images. As the second step, the analyst goes through the images, where he or she can fill in codes by either typing, or by selecting from menus, or (for counting) simply by clicking on items in the image. The tool also includes various means to simplify coding over a group of images as well as data correction. To help the biologist find items of interest in the image, the tool includes a magnifying glass, pan and zoom capabilites (where switching images will keep the same pan/zoom levels), as well as several image enhancement methods. All data is written to a file that can be opened in Excel.
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    ItemOpen Access
    A Tool Supporting the Extraction of Angling Effort Data from Remote Camera Images
    (2013-12-10) Greenberg, Saul; Godin, Theresa
    Angling effort is often estimated from data captured by creel survey (prohibitively expensive to do on more than a few lakes), or aerial surveys (limited to summer effort estimates). A recent alternative method uses remote cameras to capture images of lakes at hourly intervals over long time periods. Technicians then visually analyze the thousands of generated images for features of interest (e.g., angler counts and environmental conditions), and use that data to estimate angling effort. The problem is that the visual analysis step is time-consuming, expensive, error-prone, and difficult to validate. Consequently, we elicited the strategies and best practices technicians used when analyzing images, and identified bottlenecks. We then designed software – called TIMELAPSE – to better support image analysis. In use for several years, TIMELAPSE has proven cost-effective: it significantly eases a technician’s workflow while reducing errors. TIMELAPSE is now an effective part of estimating angling effort in BC’s small lakes fisheries.