Biomimetic Principle And Methods Of Objects Recognition And Classification In Complex Scenes

Image Understanding (IU) is to study images based on human knowledge, whichfocuses on what are objects in the image, the relationship between objects, what is scene inthe image and how to apply the scene. It mainly includes two parts: object classification andrecognition in a scene, and scene description and understanding. Object recognition has theinitiative and is the base of scene description and understanding, which is to make scene beexplained well. Scene description and understanding provide the apriori information forobject recognition, which can guide the object recognition. In essence, IU derives fromcomputer vision, while combining the knowledge of artificial intelligence and cognitivescience. It has the close relation with computer vision, artificial intelligence and cognitivescience, but it is independent of them. As the base of IU, object recognition has been appliedin many fields, such as identity determination, intelligent transport management, vehicledetection, etc. Object recognition aims to make computer capable of detecting visual image,recognizing object and classifying object in complex scene. At present, there are manymethods of object recognition, such as template matching, edge detection, statistic methodand so on. However, they lack of intelligence compared with biological visual system.Since the1990s, Professor Shoujue Wang has studied the recognition process of human,and summarized the principle of continuity in homologous samples, called as the principle ofhomology—continuity. He applied this principle to pattern recognition and put forwardbiomimetic pattern recognition and the theory of Multi-Dimensional Space BiomimeticInformatics, which provides a new route for solving imagery thinking problems by computer.In this paper, based on the mechanism of biological visual system and combining the theoryof Multi-Dimensional Space Biomimetic Informatics, object classification and recognition inIU are studied, and the corresponding computer models are constructed. Several methods ofobject recognition are proposed for different scenes. Experimental results show the feature extracting model of object in complex scene and the method of biomimetic classification andrecognition proposed in this paper are effective and feasible.(1) Based on the knowledge of neurobiology, the model of each cerebral regioninvolved in recognizing is established respectively and a biomimetic construction method ofcategory mental imagery based on the recognition mechanism of visual cortex of humanbrain is proposed. The model and algorithm are tested using training set and test setcomposed of real images. The results show that this method can establish valid deeprepresentation of these samples, based on which the biomimetic construction of categorymental imagery can be achieved.(2) The mental imagery in psychology has strong comparability with cognitiveinformation processing. In this paper, mental imagery system is linked with visual cognitivesystem, and the activity status of cells in each brain region in recognition process is found. Itis considered that the establishment of mental imagery derives from the activity status ofmany nerve cells acquired in recognition process, which is the source and base of mentalimagery construction, called as imagery basis. By the activity status of cells and their modememory and analysis in depth, imagery basis is extracted.(3) Combining the hot research results of neurobiology on visual cortex, the invariancein object recognition is introduced to determine the object category of deep presentation ofmental imagery. The shape tuning and category tuning characteristic of cells in ventral visualpathway are employed to weigh the specificity and invariance of visual cortex cells.(4) Codebook multidimensional space is constructed using Bag of words model. Imagevectors are projected to sample points in Codebook multidimensional space. Based on theprinciple of homology continuity in multidimensional space biomimetic informatics, theoptimal classification of different kinds of objects in Codebook multidimensional space isobtained using neural network classifier. A biomimetic classification and recognition methodof specific object in complex scene is proposed. Experiments are performed to investigatethe factors influencing the performance of classifier and their variation. The experimentalresults obtained by this method are compared with those obtained by the traditional methods, and results show the method proposed in this paper is valid and feasible.(5) The robust representation of image is established by Histogram of Oriented Gradient(HOG). According to the processing mechanism of human visual system and the theory ofmultidimensional space biomimetic informatics, two biomimetic classification andrecognition methods of human behavior are proposed, which are based on HOG+SVM andHOG+RBPNN respectively. The methods proposed in this paper are evaluated and comparedwith other commonly used methods. Results show that, for the classification and recognitionof human behavior in still image, the proposed methods have better performance inrecognizing different kinds of behavior, but the performance in recognizing similar behaviorsstill needs improvement.To sum up, a biomimetic classification and recognition method of specific object incomplex scene is proposed based on the processing mechanism of human visual system andthe theory of multidimensional space biomimetic informatics, which can provide a referencefor the research on other object recognition methods and multidimensional space biomimeticinformatics.