TL;DR: A series of experiments demonstrated that in images neither the wavelength of the stimulus nor the energy at each wavelength determines the color, and this departure from what the authors expect on the basis of colorimetry is complete.
Abstract: In the Color Vision Symposium at the Academy in April 1958, we showed a series of experiments which demonstrated that "4whereas in color-mixing theory the wavelengths of the stimuli and the energy content at each wavelength are significant in determining the sense of color . . . in images neither the wavelength of the stimulus nor the energy at each wavelength determines the color. This departure from what we expect on the basis of colorimetry is not a small effect, but is complete . .. .' (1, 2). The initial and most engaging experiment comprised taking two black-and-white photographs of the same scene, one through a red filter and one through a green filter, and projecting these two black-and-white pictures in superposition on the screen to yield a single black-and-white panchromatic image of the scene. When a red filter was placed in the path of the light from the projector that contained the picture taken through a red filter, the whole scene became dramatically colored as if in many respects it were a standard full-color photograph. The first paradox was that the radiation coming to the eye of the observer consisted only of various ratios of red light to white light which should have yielded only a variety of pinks. The second paradox was that the overall ratio of light from the one projector to light from the other projector could be changed markedly without changing the color names of the objects in the colored picture: the colors of the individual objects must be determined by the ratio of red light to white light, but a change in the overall ratio of red light to white light did not change the colors. In light of the understanding which we now have, this simple experiment, which was a shock to the intuitive understanding of all of us, turns out to be the most sophisticated experiment we could have undertaken. For the flavor of the many experiments described at the Symposium, I refer you to the two papers (1, 2) at that time. Here, I want to turn to the quantitative procedures which we now use. We prepared a laboratory display which we dubbed a "Mondrian" (although it actually is closer to a van Doesburg), utilizing about 100 colored papers. A paper of a given color would appear many times in different parts of the display, each time having a different size and shape and each time being surrounded by a different set of other colored papers. One reason for the design was to prohibit the superposition of afterimages of areas onto other areas (3), and another reason for the design was to obviate explanations of results in terms of the size or shape or surrounding of any given paper. The Mondrian is illuminated by using three 35-mm slide projectors with no slides in the slide holder. The output of each projector/illuminator is controlled independently. An interference filter passing long waves is placed in the path of one projector, a middle wave filter, in the path of the second, and a short-wave filter, in the path of the third (Fig. 1). One may think of these as relating roughly to the three visual pigments. A telescopic photometer (Spectra Pritchard photometer, model 1980A), placed roughly where the observers will be, receives and measures radiation from about 1/16th of a square inch on each chosen area of the Mondrian when it is pointed at that area. The instrument is calibrated so that at any wavelength it reports directly in watts per steradian per square meter. Let me call your attention to these four papers: yellow, white, green, and blue. The telescope is pointed at a yellow paper. The short-wave and middle-wave illuminators are turned off, and the whole Mondrian is illuminated with the long-wave illuminator. The output of this projector is then changed until the meter reads exactly "one" (0.1 W per Sr2 per m2). The longwave illuminator is turned off and the middle-wave illuminator is turned on. Its output is adjusted until the meter reads one. This ensures that the amount of middle-wave energy now reaching the meter from that small patch is equal to the amount of long-wave energy. Finally, after the middle-wave illuminator is turned off, the short-wave illuminator is turned on, and its output is set so that the meter (which we must remember is reading the radiation to our eyes) reads one. All three illuminators are now turned on. While looking at the Mondrian as a whole, we note that the yellow paper looks yellow. We now turn our attention to the white paper, pointing the telephotometer at it. We go through the same procedure of illuminating with one illuminator at a time and of setting each illuminator so that the light coming this time from the white paper to the meter, and hence to our eyes, measures one for the long wave and one for the middle wave and one for the short wave. Thus, we have arranged to have coming to our eye from the piece of white paper exactly the same flux-the same wavelength composition, the same energy composition-which a moment earlier we had arranged to have coming to our eye from the piece of yellow paper. The somewhat indigestible question is "what color will the piece of paper be which was white in the Mondrian previously?" Keep in mind that the information now coming to our eye from that piece of paper dictates classically that, if one, one, and one coming to our eye gave yellow, then one, one, and one must again be yellow. This conviction dates back to Newton's proposition V (4):
TL;DR: The neurophysiology of abstract and representational art can be found in this paper, where the authors present a neurobiological analysis of the brain's quest for essentials and its relationship with art.
Abstract: PART I: A FUNCTION OF THE BRAIN AND OF ART 1. The brain's quest for essentials 2. Art's quest for essentials 3. The myth of the "seeing eye" 4. A neurobiological appraisal of Vermeer and Michaelangelo 5. The neurology of the Platonic Ideal 6. The Cubist search for essentials 7. The modularity of vision 8. Seeing and understanding 9. The modularity of visual aesthetics 10. The pathology of the Platonic Ideal and the Hegelian concept PART II: THE ART OF THE RECEPTIVE FIELD 11. The receptive field 12. Mondrian, Malevich, and the neurophysiology of oriented lines 13. Mondrian, Ben Nicholson, Malevich, and the neurophysiology of squares and rectangles 14. Perceptual problems created by the receptive fields 15. The neurophysiology of the Metamalevich and the Metakandinsky 16. Kinetic art PART III: A NEUROLOGICAL EXAMINATION OF SOME ART FORMS 17. Face imperception or a portrait of prosopagnosia 18. The physiology of colour vision 19. The fauvist brain 20. The neurology of abstract and representational art 21. Monet's brain
TL;DR: Roy and Teh as discussed by the authors used Mondrian processes to construct ensembles of random decision trees called Mondrian forests, which can be grown in an incremental/online fashion and remarkably, the distribution of online Mondrian forest is the same as that of batch Mondrian tree.
Abstract: Ensembles of randomized decision trees, usually referred to as random forests, are widely used for classification and regression tasks in machine learning and statistics. Random forests achieve competitive predictive performance and are computationally efficient to train and test, making them excellent candidates for real-world prediction tasks. The most popular random forest variants (such as Breiman's random forest and extremely randomized trees) operate on batches of training data. Online methods are now in greater demand. Existing online random forests, however, require more training data than their batch counterpart to achieve comparable predictive performance. In this work, we use Mondrian processes (Roy and Teh, 2009) to construct ensembles of random decision trees we call Mondrian forests. Mondrian forests can be grown in an incremental/online fashion and remarkably, the distribution of online Mondrian forests is the same as that of batch Mondrian forests. Mondrian forests achieve competitive predictive performance comparable with existing online random forests and periodically retrained batch random forests, while being more than an order of magnitude faster, thus representing a better computation vs accuracy tradeoff.
TL;DR: A novel class of distributions, called Mondrian processes, which can be interpreted as probability distributions over kd-tree data structures, and it is shown how the process can be used as a nonparametric prior distribution in Bayesian models of relational data.
Abstract: We describe a novel class of distributions, called Mondrian processes, which can be interpreted as probability distributions over kd-tree data structures. Mondrian processes are multidimensional generalizations of Poisson processes and this connection allows us to construct multidimensional generalizations of the stick-breaking process described by Sethuraman (1994), recovering the Dirichlet process in one dimension. After introducing the Aldous-Hoover representation for jointly and separately exchangeable arrays, we show how the process can be used as a nonparametric prior distribution in Bayesian models of relational data.
TL;DR: This thesis is that efficient NMP calls for an algorithm-hardware co-design that favors algorithms with sequential accesses to enable simple hardware that accesses memory in streams, and introduces an instance of such a co-designed NMP architecture for data analytics, the Mondrian Data Engine.
Abstract: The increasing demand for extracting value out of ever-growing data poses an ongoing challenge to system designers, a task only made trickier by the end of Dennard scaling As the performance density of traditional CPU-centric architectures stagnates, advancing compute capabilities necessitates novel architectural approaches Near-memory processing (NMP) architectures are reemerging as promising candidates to improve computing efficiency through tight coupling of logic and memory NMP architectures are especially fitting for data analytics, as they provide immense bandwidth to memory-resident data and dramatically reduce data movement, the main source of energy consumptionModern data analytics operators are optimized for CPU execution and hence rely on large caches and employ random memory accesses In the context of NMP, such random accesses result in wasteful DRAM row buffer activations that account for a significant fraction of the total memory access energy In addition, utilizing NMP's ample bandwidth with fine-grained random accesses requires complex hardware that cannot be accommodated under NMP's tight area and power constraints Our thesis is that efficient NMP calls for an algorithm-hardware co-design that favors algorithms with sequential accesses to enable simple hardware that accesses memory in streams We introduce an instance of such a co-designed NMP architecture for data analytics, the Mondrian Data Engine Compared to a CPU-centric and a baseline NMP system, the Mondrian Data Engine improves the performance of basic data analytics operators by up to 49x and 5x, and efficiency by up to 28x and 5x, respectively