A 3D descriptor to detect task-oriented grasping points in clothing

© 2016. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/Manipulating textile objects with a robot is a challenging task, especially because the garment perception is difficult due to the endless configurations it can adopt, coupled with a large variety of colors and designs. Most current approaches follow a multiple re-grasp strategy, in which clothes are sequentially grasped from different points until one of them yields a recognizable configuration. In this work we propose a method that combines 3D and appearance information to directly select a suitable grasping point for the task at hand, which in our case consists of hanging a shirt or a polo shirt from a hook. Our method follows a coarse-to-fine approach in which, first, the collar of the garment is detected and, next, a grasping point on the lapel is chosen using a novel 3D descriptor. In contrast to current 3D descriptors, ours can run in real time, even when it needs to be densely computed over the input image. Our central idea is to take advantage of the structured nature of range images that most depth sensors provide and, by exploiting integral imaging, achieve speed-ups of two orders of magnitude with respect to competing approaches, while maintaining performance. This makes it especially adequate for robotic applications as we thoroughly demonstrate in the experimental section.Peer ReviewedPostprint (author's final draft

No experimental evidence for local competition in the nestling phase as a driving force for density-dependent avian clutch size

1. In birds, local competition for food between pairs during the nestling phase may affect nestling growth and survival. A decrease in clutch size with an increase in breeding density could be an adaptive response to this competition. To investigate whether breeding density causally affected the clutch size of great tits (Parus major), we manipulated breeding density in three out of eight study plots by increasing nest-box densities. We expected clutch size in these plots to be reduced compared to that in control plots. 2. We analysed both the effects of variation in annual mean density (between-year comparisons) and experimental density (within-year comparison between plots) on clutch size variation, the occurrence of second broods and nestling growth. We examined within-female variation in clutch size to determine whether individual responses explain the variation over years. 3. Over the 11 years, population breeding density increased (from 0·33 to 0·50 pairs ha–1) while clutch size and the occurrence of second broods decreased (respectively from 10·0 to 8·5 eggs and from 0·39 to 0·05), consistent with a negative density-dependent effect for the whole population. Nestling growth showed a declining but nonsignificant trend over years. 4. The decline in population clutch size over years was primarily explained by changes occurring within individuals rather than selective disappearance of individuals laying large clutches. 5. Within years, breeding density differed significantly between manipulated plots (0·16 pairs ha–1 vs. 0·77 pairs ha–1) but clutch size, occurrence of second broods and nestling growth were not affected by the experimental treatment, resulting in a discrepancy between the effects of experimental and annual variation in density on reproduction. 6. We discuss two hypotheses that could explain this discrepancy: (i) the decline in breeding performance over time was not due to density, but resulted from other, unknown factors. (ii) Density did cause the decline in breeding performance, but this was not due to local competition in the nestling phase. Instead, we suggest that competition acting in a different phase (e.g. before egg laying or after fledgling) was responsible for the density effect on clutch size among years.

Manipulating Attributes of Natural Scenes via Hallucination

In this study, we explore building a two-stage framework for enabling users to directly manipulate high-level attributes of a natural scene. The key to our approach is a deep generative network which can hallucinate images of a scene as if they were taken at a different season (e.g. during winter), weather condition (e.g. in a cloudy day) or time of the day (e.g. at sunset). Once the scene is hallucinated with the given attributes, the corresponding look is then transferred to the input image while preserving the semantic details intact, giving a photo-realistic manipulation result. As the proposed framework hallucinates what the scene will look like, it does not require any reference style image as commonly utilized in most of the appearance or style transfer approaches. Moreover, it allows to simultaneously manipulate a given scene according to a diverse set of transient attributes within a single model, eliminating the need of training multiple networks per each translation task. Our comprehensive set of qualitative and quantitative results demonstrate the effectiveness of our approach against the competing methods.Comment: Accepted for publication in ACM Transactions on Graphic

Lunar cycles of reproduction in the clown anemonefish Amphiprion percula: individual-level strategies and population-level patterns

Lunar cycles of reproduction are a widespread phenomenon in marine invertebrates and vertebrates. It is common practice to infer the adaptive value of this behavior based on the population level pattern. This practice may be flawed if individuals within the population are employing different reproductive strategies. Here, we capitalize on a long-term field study and a carefully controlled laboratory experiment of individually identifiable clown anemonefish, Amphiprion percula, to investigate the individual reproductive strategies underlying population-level patterns of reproduction. The field data reveal that A. percula exhibit a lunar cycle of reproduction at the population level. Further, the field data reveal that there is naturally occurring variation among individuals and within individuals in the number of times they reproduce per month. The laboratory experiment reveals that the number of times individuals reproduce per month is dependent on their food availability. Individuals are employing a conditional strategy, breeding once, twice or thrice per month, depending on resource availability. Breaking down the population level pattern by reproductive tactic, we show that each reproductive tactic has its own non-random lunar cycle of reproduction. Considering the adaptive value of these cycles, we suggest that all individuals, regardless of tactic, may avoid reproducing around the new moon. Further, individuals may avoid breeding in synchrony with each other, because of negative frequency dependent selection at the time of settlement. Most importantly, we conclude that determining what individuals are doing is a critical step toward understanding the adaptive value of lunar cycles of reproduction