You are presented with multiple paper abstracts, alongside the associated literature review and chapter titles. Given the provided information, you are going to do a literature review. Please generate a coherent literature review that synthesizes the content, draws connections between different works, highlights major findings, and identifies any gaps in the existing research.

Literature Review Title: Visual Attention for Robotic Cognition: A Survey 
Chapter Title:  III. COMPUTATIONAL MODELS OF VISUAL ATTENTION AND THE REQUIREMENTS OF ROBOTIC VISUAL ATTENTION 
1. Abstract of Cited Paper (BIB001):  A visual attention system, inspired by the behavior and the neuronal architecture of the early primate visual system, is presented. Multiscale image features are combined into a single topographical saliency map. A dynamical neural network then selects attended locations in order of decreasing saliency. The system breaks down the complex problem of scene understanding by rapidly selecting, in a computationally efficient manner, conspicuous locations to be analyzed in detail. Index Terms—Visual attention, scene analysis, feature extraction, target detection, visual search. ———————— F ———————— 
2. Abstract of Cited Paper (BIB002):  Most models of visual search, whether involving overt eye movements or covert shifts of attention, are based on the concept of a saliency map, that is, an explicit two-dimensional map that encodes the saliency or conspicuity of objects in the visual environment. Competition among neurons in this map gives rise to a single winning location that corresponds to the next attended target. Inhibiting this location automatically allows the system to attend to the next most salient location. We describe a detailed computer implementation of such a scheme, focusing on the problem of combining information across modalities, here orientation, intensity and color information, in a purely stimulus-driven manner. The model is applied to common psychophysical stimuli as well as to a very demanding visual search task. Its successful performance is used to address the extent to which the primate visual system carries out visual search via one or more such saliency maps and how this can be tested.

Literature Review:
Among the computational models of visual attention, the models proposed in computer vision gained widespread popularity in robotics. Specially, the computer vision models proposed in BIB001 , BIB002 ,  , and BIB003 have strong influence on the robotic model of visual attention. This is mostly because the strategies of computer vision models to analyze visual features make them suitable to be applied on the technical system (unlike the model proposed in computational neuroscience). Majority of the existing computer vision model, however, have some characteristics which impose some restrictions on their direct use for robotic visual attention. This section first summarizes the general properties of the computer vision models of visual attention and then sheds light on the issues that restrict their direct use in the robotic systems.