![]() ![]() Rather, the effect appears to be driven by the meaning of objects and scenes. Across all of these studies, consistent objects on scenes were named more accurately than inconsistent ones (“scene consistency effect”)-which cannot be explained in terms of response bias or similarity in low-level features or shape between objects and scenes 11. ![]() Therefore, in recent years, scene context effects were investigated using an object naming paradigm, where observers type in the name of an object after seeing it for a short time superimposed on (or embedded in) a naturalistic scene background 10, 11, 12, 13, 14, 15. ![]() However, these early studies were criticized for not taking response biases into account 7, 8 (for a review, see 9). Over the course of our lifetime, we have acquired knowledge of these co-occurrences of objects, scenes and locations within scenes that help us, among other things, in searching for and recognizing objects 1, 2, 3.įor example, early behavioral studies used line drawings in a forced choice paradigm to show that a consistent object within its scene context (e.g., a fire hydrant on the street) is detected faster and more accurately compared to an inconsistent object (e.g., a sofa on the street) 4, 5, 6. Additionally, objects tend to occur at particular locations within these spaces, for example, the pot is rather sitting on the stove than on the kitchen floor. For instance, a pot is more likely encountered in the kitchen than in the bathroom and a fire hydrant will rather be seen on the street than in the living room. This context is not random but particular objects tend to occur in particular spaces or “scene contexts” with varying likelihoods. We almost never see objects in isolation, but virtually always within a rich visual context. Our findings show that contextual materials indeed affect object processing-even in the absence of spatial scene structure and object content-suggesting that material is one of the contextual “ingredients” driving scene context effects. Critically, objects on materials triggered N300/N400 responses of similar magnitudes. In Experiment 2, we recorded event-related potentials and found N300/N400 responses-markers of semantic violations-for objects on inconsistent relative to consistent scenes. Also, we did not find any consistency effect for scrambled materials that served as color control condition. In Experiment 1, consistent objects on scenes were named more accurately than inconsistent ones, while there was only a marginal consistency effect for objects on materials. pinecone) superimposed on scenes (e.g., a bathroom) and close-ups of materials (e.g., tiles). To this end, we presented photographs of consistent and inconsistent objects (e.g., perfume vs. Here, we address the question of whether the materials that frequently occur in scenes (e.g., tiles in a bathroom) associated with specific objects (e.g., a perfume) are relevant for the processing of that object. To the best of our knowledge this is the firstĪpplication of intrinsic volumes to algorithm design.While scene context is known to facilitate object recognition, little is known about which contextual “ingredients” are at the heart of this phenomenon. Both algorithms make significant use of ideasįrom the field of integral geometry, most notably the notion of intrinsic Every round the learner is provided an adversarially-chosenĬontext $u_t \in \mathbb(\log T)$ and matching the known lower bounds (up to a InĬontextual search, a learner is trying to learn the value of a hidden vector $v Of binary search that captures many problems in contextual decision-making. Download a PDF of the paper titled Contextual Search via Intrinsic Volumes, by Renato Paes Leme and Jon Schneider Download PDF Abstract: We study the problem of contextual search, a multidimensional generalization ![]()
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