Abstract:Based on the previous attention selection model with visual memory as top-down guidance, a visual memory model is put forward with online learning and forgetting, called amnesic incremental hierarchical discriminant regression (AIHDR) tree, to mimic human short-term memory (STM) and long-term memory (LTM). A self-supervised competition neural network (SSCNN) combines the information from both bottom-up and top-down to find out the focus of attention (FoA). The connection weights in SSCNN can be updated in real-time according to the environment. Experimental results show that the proposed model can mimic the shift of human attention and stare at an interesting object consciously when environment changes.
过晨雷,张立明. 带有遗忘的视觉记忆模型及其在注意力选择上的应用*[J]. 模式识别与人工智能, 2008, 21(3): 381-387.
GUO Chen-Lei, ZHANG Li-Ming. A Visual Memory Model with Amnesic Function and Its Application in Attention Selection. , 2008, 21(3): 381-387.
[1] Treisman A M, Gelade G. A Feature-Integration Theory of Attention. Cognitive Psychology, 1980, 12(1): 97-136 [2] Wolfe J M. Guided Search 2.0: A Revised Model of Visual Search. Psychonomic Bulletin & Review, 1994, 1(2): 202-238 [3] Koch C, Ullman S. Shifts in Selective Visual Attention: Towards the Underlying Neural Circuitry. Human Neurobiology, 1985, 4(4): 219-227 [4] Itti L, Koch C, Niebur E. A Model of Saliency-Based Visual Attention for Rapid Scene Analysis. IEEE Trans on Pattern Analysis and Machine Intelligence, 1998, 20(11): 1254-1259 [5] Lee K W, Buxton H, Feng Jianfeng. Cue-Guided Search: A Computational Model of Selective Attention. IEEE Trans on Neural Networks, 2005, 16(4): 910- 924 [6] Downing P E. Interactions between Visual Working Memory and Selective Attention. Psychological Science, 2000, 11(6): 467-473 [7] Moores E, Laiti L, Chelazzi L. Associative Knowledge Controls Deployment of Visual Selective Attention. Nature Neuroscience, 2003, 6(2): 182-189 [8] Guo Chenlei, Zhang Liming. Attention Selection with Self-Supervised Competition Neural Network and Its Applications in Robot // International Symposium on Neural Networks. Nanjing, China, 2007: 722-732 [9] Weng Juyang, Hwang W S. Incremental Hierarchical Discriminant Regression. IEEE Trans on Neural Networks, 2007, 18(2): 397-415 [10] Lowe D G. Distinctive Image Features from Scale-Invariant Keypoints. International Journal of Computer Vision, 2004, 60(2): 91-110 [11] Walther D, Rutishauser U, Koch C, et al. Selective Visual Attention Enables Learning and Recognition of Multiple Objects in Cluttered Scenes. Computer Vision and Image Understanding, 2005, 100(1/2): 41-63 [12] Gold J M, Murray R F, Sekuler A B, et al. Visual Memory Decay Is Deterministic. Psychological Science, 2005, 16(10): 769-774