Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Incorporating models of human perception into the process of scene interpretation and object recognition in visual content is a strong trend in computer vision.   tackle the modeling of visual perception via automatic visual saliency maps for object recognition. Visual saliency represents an efficient way to drive the scene analysis towards particular areas considered 'of interest' for a vier and an efficient alternative to computationally intensive sliding window methods for object recognition. Using saliency maps,  consider biologically inspired independent paths of central and peripheral vision and apply them to fundamental steps of the so-called Bag-of-Words (BoW) paradigm, such as features sampling, pooling and encoding. Our proposal has been evaluated addressing the challenging task of active object recognition, and the results show that our method not only improves the baselines, but also achieves state-of-the-art performance in various datasets at very competitive computational times. HighlightsPerceptual model that incorporates visual attention to the problem of active object recognition.Modeling of foveal and peripheral pathways in retina.Saliency-based non-uniform feature sampling in a variable-resolution space.Saliency-sensitive Coding of features.Saliency-based Pooling of features.
['Iván González-Díaz', 'Vincent Buso', 'Jenny Benois-Pineau']
I am writing a research paper on a idea Perceptual modeling in the problem of active object recognition in visual scenes
[{"from": "human", "value": "I am writing a research paper on a idea Perceptual modeling in the problem of active object recognition in visual scenes"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Incorporating models of human perception into the process of scene interpretation and object recognition in visual content is a strong trend in computer vision.   tackle the modeling of visual perception via automatic visual saliency maps for object recognition. Visual saliency represents an efficient way to drive the scene analysis towards particular areas considered 'of interest' for a vier and an efficient alternative to computationally intensive sliding window methods for object recognition. Using saliency maps,  consider biologically inspired independent paths of central and peripheral vision and apply them to fundamental steps of the so-called Bag-of-Words (BoW) paradigm, such as features sampling, pooling and encoding. Our proposal has been evaluated addressing the challenging task of active object recognition, and the results show that our method not only improves the baselines, but also achieves state-of-the-art performance in various datasets at very competitive computational times. HighlightsPerceptual model that incorporates visual attention to the problem of active object recognition.Modeling of foveal and peripheral pathways in retina.Saliency-based non-uniform feature sampling in a variable-resolution space.Saliency-sensitive Coding of features.Saliency-based Pooling of features."}]