隨著3D電影和遊戲的蓬勃發展，雙目（立體）顯示設備日益流行，也變得更為廉價。 立體顯示設備 引入了一個額外的圖像空間，使得用於顯示的圖像域翻倍(一個圖像域對應左眼，另一個對應右眼)。 目前的雙目(立體)顯示設備主要把這個額外的圖像空間用於顯示三維立體信息。 / 人們的雙目視覺系統不僅可以把雙眼看到的具有深度差異信息的兩個圖像融合起來，而且可以把兩個在亮度，色彩， 對比度，甚至是內容細節上有一定程度不同的圖像融合到一起，形成一個單一的視界。 這個現象叫做雙眼單視界（Binocular Single Vision）。通過一些列複雜的神經生理融合過成，人們可以通過雙眼單視界比只用任意一隻單眼 觀察到更多視覺內容和信息，其獲得的信息量也多於兩個視野的線性組合。 / 在本畢業論文中，雙眼單視界首次被應用到了計算機圖形學領域，基於這一現象，提出了一個新穎的雙目色調映射框架(Binocular Tone Mapping Framework)。對於輸入的高動態範圍(High-Dynamic Range, HDR)圖像，我們的雙目色調映射 構架將生成一組用於雙目觀看的低動態範圍(Low-Dynamic Range, LDR)圖像對，用以從原HDR圖像中保留 更多的人們可感知到的視覺內容和信息。 給定任意一個指定的色調映射方法，我們的雙目計算框架首先通過使用其默認或者 人工選擇的參數生成一張LDR圖像(不失一般性，我們指定為左視野圖)，隨後，圖像對中的另一張LDR圖像 將由系統從同一HDR圖像源使用最優化算法生成。 結果的兩張LDR圖像是不相同的，它們分別保留了不同的視覺信息。通過使用雙目顯示設備，它們可以合計表現出比任一單張LDR圖像更豐富的圖像內容。 / 人們的兩個視野對圖像差異不是無限的，也存在一個容忍度。一旦超過了某個限制閾值，視覺上的不適感覺就會出現。 了避免不適 的產生，我們設計了一個全新的雙目視覺舒適預測預器(Binocular Viewing Comfort predictor)用以預測 雙目視覺的不舒適閾值。 在我們的雙目色調映射構架中，BVCP用於指導LDR圖像對的生成，同時避免觸發 任何視覺不適。 通過一些列的實驗和用戶調查，我們提出的工作框架的有效性以及BVCP預測不適閾值的準確程度都得到了驗證。 / With the booming of 3D movies and video games, binocular (stereo) display devices become more and more popular and affordable. By introducing one additional image space, stereo displays double the image domains for visualization, one for the left eye and the other for the right eye. Existing binocular display systems only utilize this dual image domain for stereopsis. / Our human binocular vision is not only able to fuse two images with disparity, but also two images with difference in luminance, contrast and even detail, into a single percept, up to a certain limit. This phenomenon is known as binocular single vision. By a complicated neurophysiologic fusion process, humans can perceive more visual content via binocular single vision than one arbitrary single view or the linear blending of two views. / In this thesis, for the first time, binocular single vision has been utilized into computer graphics. Based on this phenomenon, a novel binocular tone mapping framework is proposed. From the source high-dynamic range (HDR) image, the proposed framework generates a binoc- ular low-dynamic range (LDR) image pair that preserves more human- perceivable visual content than a single LDR image using the additional image domain. Given a tone mapping method, our framework firstly generates one tone-mapped LDR image (left, without loss of generality) by the default or user selected parameters. Then its counterpart image (right) of the LDR pair is optimally synthesized from the same source HDR image. The two LDR images are not identical, and contain different visual information. Via binocular displays, they can aggregately present more human-perceivable visual richness than a single arbitrary LDR image. / Human binocular vision has a tolerance on the difference between two views. When such limit is exceeded, binocular viewing discomfort appears. To prevent such visual discomfort, a novel binocular view- ing comfort predictor (BVCP) is also proposed to predict the comfort threshold of binocular vision. In our framework, BVCP is used to guide the generation of LDR image pair without triggering visual discomfort. Through several user studies, the effectiveness of the proposed framework in increasing human-perceivable visual richness and the pre- dictability of the proposed BVCP in predicting the binocular discomfort threshold have been demonstrated and validated. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Yang, Xuan. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2012. / Includes bibliographical references (leaves 108-115). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese. / Abstract --- p.i / Acknowledgement --- p.ix / Chapter 1 --- Introduction --- p.1 / Chapter 2 --- Background Study --- p.5 / Chapter 2.1 --- Stereo Display --- p.5 / Chapter 2.2 --- HDR Tone Mapping --- p.9 / Chapter 2.2.1 --- HDR lmage --- p.9 / Chapter 2.2.2 --- Tone Mapping --- p.11 / Chapter 3 --- Binocular Vision --- p.16 / Chapter 3.1 --- Binocular Single Vision --- p.16 / Chapter 3.1.1 --- Binocular Single Vision --- p.16 / Chapter 3.1.2 --- Motor Fusion and Sensory Fusion --- p.19 / Chapter 3.1.3 --- Fusion, Suppression and Rivalry --- p.21 / Chapter 3.1.4 --- Rivalry --- p.23 / Chapter 3.1.5 --- Fusional Theory --- p.24 / Chapter 3.1.6 --- Fusion with Stereopsis --- p.27 / Chapter 3.2 --- Binocular discomfort --- p.29 / Chapter 3.2.1 --- Fusional area --- p.31 / Chapter 3.2.2 --- Contour difference --- p.32 / Chapter 3.2.3 --- Failure of rivalry --- p.33 / Chapter 3.2.4 --- Contour and regional contrast --- p.34 / Chapter 4 --- Binocular Visual Comfort Predictor (BVCP) --- p.37 / Chapter 4.1 --- Introduction --- p.37 / Chapter 4.2 --- Design of BVCP --- p.40 / Chapter 4.2.1 --- Fusional Area --- p.40 / Chapter 4.2.2 --- Contour Fusion --- p.42 / Chapter 4.2.3 --- Failure of Rivalry --- p.48 / Chapter 4.2.4 --- Contour and Regional Contrast --- p.53 / Chapter 4.2.5 --- The Overall Fusion Predictor --- p.54 / Chapter 4.3 --- Experiments and User Study --- p.56 / Chapter 4.4 --- Discussion --- p.60 / Chapter 5 --- Binocular Tone Mapping --- p.62 / Chapter 5.1 --- Introduction --- p.62 / Chapter 5.2 --- Binocular Tone Mapping Framework --- p.66 / Chapter 5.2.1 --- System Overview --- p.66 / Chapter 5.2.2 --- Optimization --- p.68 / Chapter 5.3 --- Experiments and Results --- p.71 / Chapter 5.4 --- Userstudy --- p.77 / Chapter 5.4.1 --- Visual Richness --- p.77 / Chapter 5.4.2 --- Binocular Symmetry --- p.81 / Chapter 5.5 --- Discussion --- p.82 / Chapter 5.5.1 --- Incorporating Stereopsis --- p.82 / Chapter 5.5.2 --- Limitation --- p.84 / Chapter 5.5.3 --- Extension --- p.85 / Chapter 6 --- Conclusion --- p.91 / Chapter 6.1 --- Contribution --- p.91 / Chapter 6.2 --- Future Work --- p.92 / Chapter A --- More Results of Binocular Tone Mapping --- p.94 / Chapter B --- Test Sequence for BVCP --- p.103 / Bibliography --- p.108

The computational approach to the study of vision inquires directly into the sort of information processing needed to extract important information from the changing visual image---information such as the three-dimensional structure and movement of objects in the scene, or the color and texture of object surfaces. An important contribution that computational studies have made is to show how difficult vision is to perform, and how complex are the processes needed to perform visual tasks successfully. This article reviews some computational studies of vision, focusing on edge detection, binocular stereo, motion analysis, intermediate vision, and object recognition.

Before corresponding points in images taken with two cameras can be used to recover distances to objects in a scene, one has to determine the position and orientation of one camera relative to the other. This is the classic photogrammetric problem of relative orientation, central to the interpretation of binocular stereo information. Described here is a particularly simple iterative scheme for recovering relative orientation that, unlike existing methods, does not require a good initial guess for the baseline and the rotation.

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Olfactory sensing is ubiquitous across animals and important for survival. Yet, its characteristics, mechanisms, and functions in humans remain not well understood. In this dissertation, I present four studies on human olfactory perception. Study I investigates the impact of short-term exposures to an odorant on long-term olfactory learning and habituation, while Study II examines human ability to localize smells; Study III probes visual-olfactory integration of object representations, and Study IV explores the role of olfaction in sensing nutrients. Several conclusions are drawn from these studies. First, brief intermittent exposures to even a barely detectable odorant lead to long-term incremental odorant-specific habituation. Second, humans localize smells based on gradient cues between the nostrils. Third, there is a within-hemispheric advantage in the integration of visual-olfactory object representations. Fourth, olfaction partakes in nutrient-sensing and facilitates the detection of food. Some broader implications of our findings are discussed.

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No description available.

In this dissertation, I examine binocular 3D motion processing through a series of psychophysical and neuroimaging experiments aimed at uncovering the neural computations involved and their interaction with the known hierarchy of visual motion processing. Two primary binocular cues could be used to compute 3D motion: one based on changing disparities over time (CD), the other based on interocular velocity differences (IOVD). Under normal viewing conditions, both cues coexist and (potentially) provide the same 3D direction information, yet whether CD, IOVD, or both mechanisms exist has distinct implications for how 3D motion is processed along the visual stream. First, I measured 3D direction discrimination sensitivity is measured for isolated binocular cues under a range of 3D motion speeds and visual eccentricities. Comparison of isolated-cue sensitivity to corresponding combined cue sensitivity (i.e. concurrent IOVD & CD cue stimuli) provided an estimate of relative cue contributions under normal viewing conditions. Second, I conducted a series of motion adaptation experiments to differentiate the neural representation of 2D and 3D directions of motion, and examine the degree to which IOVD or CD mechanisms can account for 3D motion adaptation. Third, I examined the neural locus of 3D motion processing by measuring 3D direction- selectivity throughout a range of visual cortical areas using functional neuroimaging in an event-related paradigm that parallels psychophysical adaptation experiments. Finally, I discuss the broader implications for the neural mechanisms of binocular 3D motion processing and future experimental directions. Together, these results reveal that: (1) the IOVD cue is the dominant cue to 3D motion processing across the majority of natural speeds & eccentricities, (2) neural tuning for 3D motion is distinct from 2D motion and can be fully explained by an IOVD mechanism, and (3) the IOVD cue is computed relatively late in the visual processing stream, in areas MT & MST— cortical areas primarily associated with 2D/retinal motion and thought to be beyond the point of binocular combination. The significance of IOVD —but not CD—cues to 3D motion perception motivates a drastic modification to canonical models of motion processing to include the late-stage comparison of eye- specific motion signals. / text

Active binocular vision systems are powerful tools in machine vision. With a virtually unlimited field-of-view they have access to huge amounts of information, yet are able to confine their resources to specific regions of interest. Since they can dynamically interact with the environment, they are able to successfully address problems that are ill-posed to passive systems. A primary goal of an active binocular vision systems is to ascertain depth information. Since they employ two cameras and are able to sample a scene from two distinct vantage points, they are well suited for such a task. The depth recovery process is composed of two interrelated components: image registration and sampling. Image registration is the process of determining corresponding points between the stereo images. Once points in the images have been matched, 3D information can be recovered via triangulation. Image sampling determines how the image is discretized and represented. Image registration and sampling are highly interdependent. The choice of sampling scheme can profoundly impact the accuracy and complexity of the registrations process. In many situations, particular registration algorithms are simply incompatible with some sampling schemes. In this dissertation we meticulously address both registration and sampling in the context of stereopis for active binocular vision systems. Throughout the development of this work, contributions in each area are addressed with an eye toward their eventual integration into a cohesive registration procedure appropriate for active binocular vision systems. The actual synthesis is a daunting task that is beyond the scope of this single dissertation. The focus of this work is to assiduously analyze both registration and sampling, establishing a solid foundation for their future aggregation. One of the most successful approaches to image registration is phase-differencing. Phase-differencing algorithms provide a fast, powerful means for depth recovery. Unfortunately, phase-differencing techniques suffer from two significant impediments: phase nonlinearities and neglect of multispectral information. This dissertation uses the amenable properties of white noise images to analytically quantify the behavior of phase in these regions of phase nonlinearity. The improved understanding gained from this analysis enables us to create a new, more effective method for identifying these regions based on the second derivative of phase. We also suggest a novel approach that combines our method of nonlinear phase detection with strategies of both phase-differencing and local correlation. This hybrid approach retains the advantageous properties of phase-differencing while incorporating the multispectral aspects of local correlation. This task of registration is greatly simplified if the camera geometry is known and the search for corresponding points can be restricted to epipolar lines. Unfortunately, computation of epipolar lines for an active system requires calibration which can be both highly complex and inaccurate. While it is possible to register images without calibration information, such unconstrained algorithms are usually time consuming and prone to error. In this dissertation we propose compromise. Even without the instantaneous knowledge of the system geometry, we can restrict the region of correspondence by imposing limits on the possible range of configurations, and as a result, confine our search for matching points to what we refer to as epipolar spaces. For each point in one image, we define the corresponding epipolar space in the other image as the union of all associated epipolar lines over all possible system geometries. Epipolar spaces eliminate the need for calibration at the cost of an increased search region. Since the average size of a search space is directly related to the accuracy and efficiency of any registration algorithm, it is essential to mitigate the increase. The major contribution of this dissertation is the derivation of an optimal nonuniform sampling that minimizes the average area per epipolar space. / text

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