کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
9348892 | 1263660 | 2005 | 27 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Modeling the influence of task on attention
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کلمات کلیدی
موضوعات مرتبط
علوم زیستی و بیوفناوری
علم عصب شناسی
سیستم های حسی
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چکیده انگلیسی
We propose a computational model for the task-specific guidance of visual attention in real-world scenes. Our model emphasizes four aspects that are important in biological vision: determining task-relevance of an entity, biasing attention for the low-level visual features of desired targets, recognizing these targets using the same low-level features, and incrementally building a visual map of task-relevance at every scene location. Given a task definition in the form of keywords, the model first determines and stores the task-relevant entities in working memory, using prior knowledge stored in long-term memory. It attempts to detect the most relevant entity by biasing its visual attention system with the entity's learned low-level features. It attends to the most salient location in the scene, and attempts to recognize the attended object through hierarchical matching against object representations stored in long-term memory. It updates its working memory with the task-relevance of the recognized entity and updates a topographic task-relevance map with the location and relevance of the recognized entity. The model is tested on three types of tasks: single-target detection in 343 natural and synthetic images, where biasing for the target accelerates target detection over twofold on average; sequential multiple-target detection in 28 natural images, where biasing, recognition, working memory and long term memory contribute to rapidly finding all targets; and learning a map of likely locations of cars from a video clip filmed while driving on a highway. The model's performance on search for single features and feature conjunctions is consistent with existing psychophysical data. These results of our biologically-motivated architecture suggest that the model may provide a reasonable approximation to many brain processes involved in complex task-driven visual behaviors.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Vision Research - Volume 45, Issue 2, January 2005, Pages 205-231
Journal: Vision Research - Volume 45, Issue 2, January 2005, Pages 205-231
نویسندگان
Vidhya Navalpakkam, Laurent Itti,