Human visual system model

About: Human visual system model is a research topic. Over the lifetime, 8697 publications have been published within this topic receiving 259440 citations.

Learning a dictionary of shape-components in visual cortex: comparison with neurons, humans and machines

Abstract: In this thesis, I describe a quantitative model that accounts for the circuits and computations of the feedforward path of the ventral stream of visual cortex. This model is consistent with a general theory of visual processing that extends the hierarchical model of [Hubel and Wiesel, 1959] from primary to extrastriate visual areas. It attempts to explain the first few hundred milliseconds of visual processing and "immediate recognition". One of the key elements in the approach is the learning of a generic dictionary of shape-components from V2 to IT, which provides an invariant representation to task-specific categorization circuits in higher brain areas. This vocabulary of shape-tuned units is learned in an unsupervised manner from natural images, and constitutes a large and redundant set of image features with different complexities and invariances. This theory significantly extends an earlier approach by [Riesenhuber and Poggio, 1999a] and builds upon several existing neurobiological models and conceptual proposals. First, I present evidence to show that the model can duplicate the tuning properties of neurons in various brain areas (e.g., V1, V4 and IT). In particular, the model agrees with data from V4 about the response of neurons to combinations of simple two-bar stimuli [Reynolds et al., 1999] (within the receptive field of the S2 units) and some of the C2 units in the model show a tuning for boundary conformations which is consistent with recordings from V4 [Pasupathy and Connor, 2001]. Second, I show that not only can the model duplicate the tuning properties of neurons in various brain areas when probed with artificial stimuli, but it can also handle the recognition of objects in the real-world, to the extent of competing with the best computer vision systems. Third, I describe a comparison between the performance of the model and the performance of human observers in a rapid animal vs. non-animal recognition task for which recognition is fast and cortical back-projections are likely to be inactive. Results indicate that the model predicts human performance extremely well when the delay between the stimulus and the mask is about 50 ms. This suggests that cortical back-projections may not play a significant role when the time interval is in this range, and the model may therefore provide a satisfactory description of the feedforward path. Taken together, the evidences suggest that we may have the skeleton of a successful theory of visual cortex. In addition, this may be the first time that a neurobiological model, faithful to the physiology and the anatomy of visual cortex, not only competes with some of the best computer vision systems thus providing a realistic alternative to engineered artificial vision systems, but also achieves performance close to that of humans in a categorization task involving complex natural images. (Copies available exclusively from MIT Libraries, Rm. 14-0551, Cambridge, MA 02139-4307. Ph. 617-253-5668; Fax 617-253-1690.)

Confuse Your Illusion Feedback to Early Visual Cortex Contributes to Perceptual Completion

Abstract: A striking example of the constructive nature of visual perception is how the human visual system completes contours of occluded objects. To date, it is unclear whether perceptual completion emerges during early stages of visual processing or whether higher-level mechanisms are necessary. To answer this question, we used transcranial magnetic stimulation to disrupt signaling in V1/V2 and in the lateral occipital (LO) area at different moments in time while participants performed a discrimination task involving a Kanizsa-type illusory figure. Results show that both V1/V2 and higher-level visual area LO are critically involved in perceptual completion. However, these areas seem to be involved in an inverse hierarchical fashion, in which the critical time window for V1/V2 follows that for LO. These results are in line with the growing evidence that feedback to V1/V2 contributes to perceptual completion.

Protecting publicly-available images with an invisible image watermark

Abstract: A method is presented for marking high-quality digital images with a robust and invisible watermark. A broad definition of robustness, stated as fundamental, is used. It requires the invisible mark to survive and remain detectable through all image manipulations that in themselves does not damage the image beyond useability. These manipulations include JPEG "lossy" compression and, in the extreme, the printing and rescanning of the image. The watermark is imparted onto an image as a random, bur reproducible, small modulation of its pixel brightnesses, and becomes a permanent part of the marked image. Detecting the imparted watermark, especially after image manipulation, is a daunting task. It is one of detecting the presence of a known small modulation of a random carrier where the carrier is composed of the pixel brightness values of the unmarked image. The method presented exploits the not well understood but superb ability of the human visual system to recognize a correlated pattern in a scatter diagram called a "visualizer-coincidence image." Results of application of the method are presented.