Abstract-Recent advances in the characterization of small body surfaces with stereophotoclinometry are discussed. The principal data output is an ensemble of landmark maps (L-maps), high-resolution topography/albedo maps of varying resolution that tile the surface of the body. Because they can have a resolution comparable to the best images, and can be located on a global reference frame to high accuracy, L-maps provide a significant improvement in discriminatory power for studies of small bodies, ranging from regolith processes to interior structure. These techniques are now being used to map larger bodies such as the Moon and Mercury. L-maps are combined to produce a standard global topography model (GTM) with about 1.57 million vectors and having a wide variety of applications. They can also be combined to produce high-resolution topography maps that describe local areas with much greater detail than the GTM. When combined with nominal predictions from other data sources and available data from other instruments such as LIDAR or RADAR, solutions for the spacecraft position and camera pointing are the most accurate available. Examples are drawn from studies of Phobos, Eros, and Itokawa, including surface characterization, gravity analysis, spacecraft navigation, and incorporation of LIDAR or RADAR data. This work has important implications for potential future missions such as Deep Interior and the level of navigation and science that can be achieved.

Five experiments examined what is learned based on the perceptual and semantic information of objects in visual statistical learning (VSL). In the familiarization phase, participants viewed a sequence of line drawings and detected repetitions of various objects. In a subsequent test phase, they watched 2 test sequences (statistically related triplets vs. unrelated foils) and decided whether the first or second sequence was more familiar based on the familiarization phase. In Experiment 1A, the test sequences comprised line drawings; in Experiment 1B, they comprised word stimuli representing each line drawing. The results showed that performance for statistically related triplets was greater than chance. In Experiments 2 and 3 containing the forward ABC and backward CBA triplets in the test, the results showed the importance of temporal order, especially in line drawings. In Experiment 4, in which the forward triplets were pitted against the backward triplets, we showed that temporal order is still important for the expression of VSL with word stimuli. Finally, in Experiment 5, we replicated the results of Experiments 2 and 3 even with the images of visual objects. These results suggest the parallel processes on the visual features and semantic information of objects in VSL.

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Recent studies on logical reasoning have suggested that people are intuitively aware of the logical validity of syllogisms or that they intuitively detect conflict between heuristic responses and logical norms via slight changes in their feelings. According to logical intuition studies, logically valid or heuristic logic no-conflict reasoning is fluently processed and induces positive feelings without conscious awareness. One criticism states that such effects of logicality disappear when confounding factors such as the content of syllogisms are controlled. The present study used abstract propositions and tested whether people intuitively detect logical value. Experiment 1 presented four logical propositions (conjunctive, biconditional, conditional, and material implications) regarding a target case and asked the participants to rate the extent to which they liked the statement. Experiment 2 tested the effects of matching bias, as well as intuitive logic, on the reasoners’ feelings by manipulating whether the antecedent or consequent (or both) of the conditional was affirmed or negated. The results showed that both logicality and matching bias affected the reasoners’ feelings, and people preferred logically true targets over logically false ones for all forms of propositions. These results suggest that people intuitively detect what is true from what is false during abstract reasoning. Additionally, a Bayesian mixed model meta-analysis of conditionals indicated that people’s intuitive interpretation of the conditional “if p then q” fits better with the conditional probability, q given p.