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Copyright of Informatica (03505596) is the property of Slovene Society Informatika and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Informatica (03505596) is the property of Slovene Society Informatika and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Though an important measure for ecological studies, obtaining foraging data through direct observation is rarely assessed independently. Using field measurements (foraging habitat, food acquisition behavior, and food manipulation time), the summer diet of Whooping Cranes ( Grus americana) in Wisconsin, USA, was determined; foods consumed based on foraging behavior were identified; and ingestion for Sandhill Cranes (Antigone canadensis) was assessed. Based on 102 observations, Whooping Cranes occupying six territories consumed 17 food items (verified with images), of which 90 samples from nine foods were modeled. Food manipulation time predicted food size: ln(y) = 3.50 + 0.45 ln(x) - 0.05 ln(x2) ( r2 = 0.63, P< 0.001). Classification tree analysis identified consumed food using foraging behavior (error rate = 17%). A schematic model with the same three behavioral variables and an additional variable of direct observation identified 93% of 90 items. With Sandhill Cranes, observed swallows predicted actual swallows (y = 1.12x - 6.18 ( r2 = 0.85, 95% CI of slope = 0.79 to 1.45, 95% CI of y-intercept = -50.55 to 38.19)). Field observation of diet and ingestion can be applied to any bird species that uses open habitats where food acquisition behavior and food size vary enough to inform models of foraging behavior. [ABSTRACT FROM AUTHOR]

Video retrieval is a challenging task in computer vision, especially with complex queries. In this paper, we consider a new type of complex query which simultaneously covers person and location information. The aim to search a specific person in a specific location. Bag-Of-Visual-Words (BOW) is widely known as an effective model for presenting rich-textured objects and scenes of places. Meanwhile, deep features are powerful for faces. Based on such state-of-the-art approaches, we introduce a framework to leverage BOW model and deep features for person-place video retrieval. First, we propose to use a linear kernel classifier instead of using L2 distance to estimate the similarity of faces, given faces are represented by deep features. Second, scene tracking is employed to deal with the cases face of the query person is not detected. Third, we evaluate several strategies for fusing individual person search and location search results. Experiments were conducted on standard benchmark dataset (TRECVID Instance Search 2016) with more than 300 GB in storage and 464 hours in duration. [ABSTRACT FROM AUTHOR]