Events & Talks

Perceiving Systems Talk Irfan Essa 10-09-2015 Data-Driven Methods for Video Analysis and Enhancement In this talk, I will start with describing the pervasiveness of image and video content, and how such content is growing with the ubiquity of cameras. I will use this to motivate the need for better tools for analysis and enhancement of video content. I will start with some of our earlier work on temporal modeling of video, then lead up to some of our current work and describe two main projects. (1) Our approach for a video stabilizer, currently implemented and running on YouTube, and its extensions. (2) A robust and scaleable method for video segmentation. I will describe, in some deta... Naejin Kong

Perceiving Systems Talk Sergi Rocamora 08-09-2015 Bayesian Image-Based Rendering and Application to Stereoscopic Cinema and 3DTV Optics with long focal length have been extensively used for shooting 2D cinema and television, either to virtually get closer to the scene or to produce an aesthetical effect through the deformation of the perspective. However, in 3D cinema or television, the use of long focal length either creates a ``cardboard effect'' or causes visual divergence. To overcome this problem, state-of-the-art methods use disparity mapping techniques, which is a generalization of view interpolation, and generate new stereoscopic pairs from the two image sequences. We propose to use more than two cameras to s...

Perceiving Systems Talk Darren Cosker 02-09-2015 Applying Computer Vision and Graphics Research in Visual Effects and Entertainment The visual effects and entertainment industries are now a fundamental part of the computer graphics and vision landscapes - as well as impacting across society in general. One of the issues in this area is the creation of realistic characters, creating assets for production, and improving work-flow. Advances in computer graphics, vision and rendering have underlined much of the success of these industries, built on top of academic advances. However, there are still many unsolved problems. In this talk I will outline some of the challenges we have faced in crossing over academic research i... Silvia Zuffi

Perceiving Systems Talk Bojan Pepik 01-09-2015 Towards Richer Object Representations for Object Class Detection in Real World Images Current object class detection methods typically target 2D bounding box localization, encouraged by benchmark data sets, such as Pascal VOC. While this seems suitable for the detection of individual objects, higher-level applications, such as autonomous driving and 3D scene understanding, would benefit from more detailed and richer object hypotheses. In this talk I will present our recent work on building more detailed object class detectors, bridging the gap between higher level tasks and state-of-the-art object detectors. I will present a 3D object class detection method that can reliably...

Perceiving Systems Talk Luca del Pero 26-08-2015 Articulated motion discovery using pairs of trajectories Most computer vision systems cannot take advantage of the abundance of Internet videos as training data. This is because current methods typically learn under strong supervision and require expensive manual annotations. (e.g. videos need to be temporally trimmed to cover the duration of a specific action, object bounding boxes, etc.). In this talk, I will present two techniques that can lead to learning the behavior and the structure of articulated object classes (e.g. animals) from videos, with as little human supervision as possible. First, we discover the characteristic motion patterns o... Laura Sevilla

Perceiving Systems Talk Garrett Stanley 10-07-2015 Reading and Writing the Neural Code: Challenges in Neuroengineering The external world is represented in the brain as spatiotemporal patterns of electrical activity. Sensory signals, such as light, sound, and touch, are transduced at the periphery and subsequently transformed by various stages of neural circuitry, resulting in increasingly abstract representations through the sensory pathways of the brain. It is these representations that ultimately give rise to sensory perception. Deciphering the messages conveyed in the representations is often referred to as “reading the neural code”. True understanding of the neural code requires knowledge of not on... Jonas Wulff

Perceiving Systems Talk Trevor Darrell 26-06-2015 Perceptual representation learning across diverse modalities and domains Learning of layered or "deep" representations has provided significant advances in computer vision in recent years, but has traditionally been limited to fully supervised settings with very large amounts of training data. New results show that such methods can also excel when learning in sparse/weakly labeled settings across modalities and domains. I'll present our recent long-term recurrent network model which can learn cross-modal translation and can provide open-domain video to text transcription. I'll also describe state-of-the-art models for fully convolutional pixel-dense segmentati... Jonas Wulff

Perceiving Systems Talk Rich Zemel 10-06-2015 Learning Rich and Fair Representations from Images and Text I will talk about two types of machine learning problems, which are important but have received little attention. The first are problems naturally formulated as learning a one-to-many mapping, which can handle the inherent ambiguity in tasks such as generating segmentations or captions for images. A second problem involves learning representations that are invariant to certain nuisance or sensitive factors of variation in the data while retaining as much of the remaining information as possible. The primary approach we formulate for both problems is a constrained form of joint emb... Gerard Pons-Moll

Perceiving Systems Talk Hans-Peter Seidel 18-05-2015 3D Image Analysis and Synthesis -- The World inside the Computer During the last three decades computer graphics established itself as a core discipline within computer science and information technology. Two decades ago, most digital content was textual. Today it has expanded to include audio, images, video, and a variety of graphical representations. New and emerging technologies such as multimedia, social networks, digital television, digital photography and the rapid development of new sensing devices, telecommunication and telepresence, virtual reality, or 3D-internet further indicate the potential of computer graphics...

Perceiving Systems Talk Andrea Vedaldi 04-05-2015 Learning and understanding visual representations Learnable representations, and deep convolutional neural networks (CNNs) in particular, have become the preferred way of extracting visual features for image understanding tasks, from object recognition to semantic segmentation. In this talk I will discuss several recent advances in deep representations for computer vision. After reviewing modern CNN architectures, I will give an example of a state-of-the-art network in text spotting; in particular, I will show that, by using only synthetic data and a sufficiently large deep model, it is possible directly map image regions to Englis...

Perceiving Systems IS Colloquium Cristian Sminchisescu 24-03-2015 From Perceptual Evidence to Large-Scale Visual Recognition Models Recent progress in computer-based visual recognition heavily relies on machine learning methods trained using large scale annotated datasets. While such data has made advances in model design and evaluation possible, it does not necessarily provide insights or constraints into those intermediate levels of computation, or deep structure, perceived as ultimately necessary in order to design reliable computer vision systems. This is noticeable in the accuracy of state of the art systems trained with such annotations, which still lag behind human performance in similar tasks. Nor does the exist...

Perceiving Systems Talk Benedetta Gennaro 11-03-2015 Of Breasts and Symbols: A Visual Journey through Twenty-Five Centuries of Western Art and Culture The breast is not just a protruding gland situated on the front of the thorax in female bodies: behind biology lies an intricate symbolism that has taken various and often contradictory meanings.  We begin our journey looking at pre-historic artifacts that revered the breast as the ultimate symbol of life; we then transition to the rich iconographical tradition centering on the so-called Virgo Lactans when the breast became a metaphor of nourishment for the entire Christian community. Next, we look at how artists have eroticized the breast in portraits of fifteenth-century French court...

Perceiving Systems Talk Michael Tarr 26-02-2015 "Real stupidity beats artificial intelligence every time" (Terry Pratchett) How is it that biological systems can be so imprecise, so ad hoc, and so inefficient, yet accomplish (seemingly) simple tasks that still elude state-of-the-art artificial systems? In this context, I will introduce some of the themes central to CMU's new BrainHub Initiative by discussing: (1) The complexity and challenges of studying the mind and brain; (2) How the study of the mind and brain may benefit from considering contemporary artificial systems; (3) Why studying the mind and brain might be interesting (and possibly useful) to computer scientists.

Perceiving Systems Talk Paul G. Kry 24-02-2015 Balancing Speed and Fidelity in Physics Based Animation and Control In this talk I will give an overview of work I have done over the years exploring physically based simulation of contact, deformation, and articulated structures where there are trade-offs between computational speed and physical fidelity that can be made.  I will also discuss examples that mix data-driven and physically based approaches in animation and control.<br /> <br /> Paul Kry is an associate professor in the School of Computer Science at McGill University.  He has a BMath from University of Waterloo, and MSc and PhD from University of British Columbia.  His res...

Perceiving Systems Talk Nikolaus F. Troje 18-02-2015 What is biological motion? <p> Everyone in visual psychology seems to know what Biological Motion is. Yet, it is not easy to come up with a definition that is specific enough to justify a distinct label, but is also general enough to include the many different experiments to which the term has been applied in the past. I will present a number of tasks, stimuli, and experiments, including some of my own work, to demonstrate the diversity and the appeal of the field of biological motion perception. In trying to come up with a definition of the term, I will particularly focus on a type of motion that has been consider...

Perceiving Systems Talk Vladlen Koltun 17-02-2015 Reconstructing Complete 3D Models from Single Images We present an approach to creating 3D models of objects depicted in Web images, even when each object may only be shown in a single image. Our approach uses a comparatively small collection of existing 3D models to guide the reconstruction process. These existing shapes are used to derive information about shape structure. Our guiding idea is to jointly analyze the images and the available 3D models. Joint analysis of all images along with the available shapes regularizes the formulated optimization problems, stabilizes estimation of camera parameters and construction of dense pixel-level c...

Perceiving Systems IS Colloquium Michael Goesele 16-02-2015 Reflecting in and on the Gradient Domain Image-based rendering has been introduced in the 1990s as an alternative approach to photorealistic rendering. Its key idea is to novel renderings by re-projecting pixels from nearby views. The basic approach works well for many scenes but breaks down if the scene contains “non-standard” elements such as reflective surfaces. In this talk, I will first show how we can extend image-based rendering to handle scenes with reflections. I will then discuss a novel gradient-based technique for image-based rendering that can intrinsically handle scenes with reflections.</pre>

Perceiving Systems Symposium 10-12-2014 - 13-12-2014 Scenes from Videos Workshop This invitation-only workshop will bring together experts in the field to focus on the problem of estimating Scenes from Video. In so doing, we hope to draw several lines of research together to address the problem of extracting physical and semantic information from video.

Perceiving Systems Talk Wenzel Jakob 28-10-2014 Capturing and simulating the interaction of light with the world around us Driven by the increasing demand for photorealistic computer-generated images, graphics is currently undergoing a substantial transformation to physics-based approaches which accurately reproduce the interaction of light and matter. Progress on both sides of this transformation -- physical models and simulation techniques -- has been steady but mostly independent from another. When combined, the resulting methods are in many cases impracticably slow and require unrealistic workarounds to process even simple everyday scenes. My research lies at the interface of these two research fields; my g...

Perceiving Systems IS Colloquium Konrad Schindler 15-10-2014 Images everywhere - computer vision with vehicle-mounted, airborne and tourist cameras I will present selected research projects of the Photogrammetry and Remote Sensing Group at ETH, including (i) 3D scene flow estimation for stereo video captured from a car; (ii) extraction of road networks from aerial images; and (iii) 3D reconstruction from large, unstructured (e.g. crowd-sourced) image collections.<br />

Perceiving Systems Talk Leonid Sigal 15-09-2014 Weak-supervision for Objects Detection and Image/Video Set Summarization <p> The growing scale of image and video datasets in vision makes labeling and annotation of such datasets, for training of recognition models, difficult and time consuming. Further, richer models often require richer labelings of the data, that are typically even more difficult to obtain. In this talk I will focus on two models that make use of different forms of supervision for two different vision tasks.  <br /> <br /> In the first part of this talk I will focus on object detection. The appearance of an object changes profoundly with pose, camera view and interactions of the ...

Perceiving Systems Talk Jonathan Taylor 04-09-2014 Hands and Dolphins: Modelling Non-Rigid Shape with Subdivision Surfaces Abstract: I will present a general framework for modelling and recovering 3D shape and pose using subdivision surfaces. To demonstrate this frameworks generality, I will show how to recover both a personalized rigged hand model from a sequence of depth images and a blend shape model of dolphin pose from a collection of 2D dolphin images. The core requirement is the formulation of a generative model in which the control vertices of a smooth subdivision surface are parameterized (e.g. with joint angles or blend weights) by a differentiable deformation function. The energy function that fal...

Perceiving Systems Talk Abhilash Srikantha 29-08-2014 Discovering Object Classes from Activities <p> In order to avoid an expensive manual labeling process or to learn object classes autonomously without human intervention, object discovery techniques have been proposed that extract visual similar objects from weakly labelled videos. However, the problem of discovering small or medium sized objects is largely unexplored. We observe that videos with activities involving human-object interactions can serve as weakly labelled data for such cases. Since neither object appearance nor motion is distinct enough to discover objects in these videos, we propose a framework that samples from a s...

Perceiving Systems Talk Lourdes Agapito 22-07-2014 Reconstructing the Pascal VOC Dataset and Non-Rigid Structure from Motion: Two sides of the same problem? <p> In this talk I will discuss two related problems in 3D reconstruction: (i) recovering the 3D shape of a temporally varying non-rigid 3D surface given a single video sequence and (ii) reconstructing different instances of the same object class category given a large collection of images from that category. In both cases we extract dense 3D shape information by analysing shape variation -- in one case of the same object instance over time and in the other across different instances of objects that belong to the same class.</p> <p> First I will discuss the problem of dense capture of 3D ...

Perceiving Systems IS Colloquium Christian Theobalt 14-07-2014 4D reconstruction in complex scenes, inverse rendering, advanced video editing Even though many challenges remain unsolved, in recent years computer graphics algorithms to render photo-realistic imagery have seen tremendous progress. An important prerequisite for high-quality renderings is the availability of good models of the scenes to be rendered, namely models of shape, motion and appearance. Unfortunately, the technology to create such models has not kept pace with the technology to render the imagery. In fact, we observe a content creation bottleneck, as it often takes man months of tedious manual work by a animation artists to craft models of moving virtual sce... Gerard Pons-Moll

Perceiving Systems Talk Brian Corner 11-06-2014 Getting the People Right: A Physical Anthropologist's View of Digital Human Modeling for Virtual Environments <p> A goal in virtual reality is for the user to experience a synthetic environment as if it were real. Engagement with virtual actors is a big part of the sensory context, thus getting the people "right" is critical for success. Size, shape, gender, ethnicity, clothing, color, texture, movement, among other attributes must be layered and nuanced to provide an accurate encounter between an actor and a user. In this talk, I discuss the development of digital human models and how they may be improved to obtain the high realism for successful engagement in a virtual world.</p>

Perceiving Systems Talk Christian Häne 10-06-2014 Convex Methods for Dense Semantic 3D Reconstruction Volumetric 3D modeling has attracted a lot of attention in the past. In this talk I will explain how the standard volumetric formulation can be extended to include semantic information by using a convex multi-label formulation. One of the strengths of our formulation is that it allows us to directly account for the expected surface orientations. I will focus on two applications. Firstly, I will introduce a method that allows for joint volumetric reconstruction and class segmentation. This is achieved by taking into account the expected orientations of object classes such as ground and build...

Perceiving Systems IS Colloquium Christoph Lampert 12-05-2014 Towards Lifelong Learning for Visual Scene Understanding <p> The goal of lifelong visual learning is to develop techniques that continuously and autonomously learn from visual data, potentially for years or decades. During this time the system should build an ever-improving base of generic visual information, and use it as background knowledge and context for solving specific computer vision tasks. In my talk, I will highlight two recent results from our group on the road towards lifelong visual scene understanding: the derivation of theoretical guarantees for lifelong learning systems and the development of practical methods for object categori... Gerard Pons-Moll

Perceiving Systems Talk Nikolaus Troje 06-05-2014 Depth ambiguity and perceptual biases in biological motion perception <p> Point-light walkers and stick figures rendered orthographically and without self-occlusion do not contain any information as to their depth. For instance, a frontoparallel projection could depict a walker from the front or from the back. Nevertheless, observers show a strong bias towards seeing the walker as facing the viewer. A related stimulus, the silhouette of a human figure, does not seem to show such a bias. We develop these observations into a tool to study the cause of the facing the viewer bias observed for biological motion displays.</p> <p> I will give a short overview ab...

Perceiving Systems IS Colloquium Thomas Brox 05-05-2014 Video Segmentation Compared to static image segmentation, video segmentation is still in its infancy. Various research groups have different tasks in mind when they talk of video segmentation. For some it is motion segmentation, some think of an over-segmentation with thousands of regions per video, and others understand video segmentation as contour tracking. I will go through what I think are reasonable video segmentation subtasks and will touch the issue of benchmarking. I will also discuss the difference between image and video segmentation. Due to the availability of motion and the redundancy of successi... Gerard Pons-Moll

Perceiving Systems Talk Cordelia Schmid 30-04-2014 Large displacement optical flow & flow-based action recognition <p> In the first part of our talk, we present an approach for large displacement optical flow. Optical flow computation is a key component in many computer vision systems designed for tasks such as action<br /> detection or activity  recognition. Inspired by the large displacement optical flow of Brox and  Malik, our approach  DeepFlow  combines a novel matching algorithm with a variational approach . Our matching algorithm builds upon a multi-stage architecture interleaving convolutions and max-pooling.  DeepFlow efficiently handles large displacements&nbsp...

Perceiving Systems IS Colloquium Jiri Matas 28-04-2014 WaldBoost: Combining Sequential Analysis with Machine Learning for Solving Time-constrained Vision Problems Computer vision problems often involve optimization of two quantities, one of which is time. Such problems can be formulated as time-constrained optimization or performance-constrained search for the fastest algorithm. We show that it is possible to obtain quasi-optimal time-constrained solutions to some vision problems by applying Wald's theory of sequential decision-making. Wald assumes independence of observation, which is rarely true in computer vision. We address the problem by combining Wald's sequential probability ratio test and AdaBoost. The solution, called the WaldBoost... Gerard Pons-Moll

Perceiving Systems Talk Daniel Scharstein 10-04-2014 Scalable Surface-Based Stereo Matching Stereo matching -- establishing correspondences between images taken from nearby viewpoints -- is one of the oldest problems in computer vision.  While impressive progress has been made over the last two decades, most current stereo methods do not scale to the high-resolution images taken by today's cameras since they require searching the full space of all possible disparity hypotheses over all pixels. <p> In this talk I will describe a new scalable stereo method that only evaluates a small portion of the search space.  The method first generates plane hypotheses from mat...

Perceiving Systems Talk Stan Sclaroff 27-03-2014 Video-based Analysis of Humans and Their Behavior This talk will give an overview of some of the research in the Image and Video Computing Group at Boston University related to image- and video-based analysis of humans and their behavior, including: tracking humans, localizing and classifying actions in space-time, exploiting contextual cues in action classification, estimating human pose from images, analyzing the communicative behavior of children in video, and sign language recognition and retrieval. <p> Collaborators in this work include (in alphabetical order): Vassilis Athitsos, Qinxun Bai, Margrit Betke, R. Gokberk Cinbis, Kun He,...

Perceiving Systems IS Colloquium Edmond Boyer 20-03-2014 Multi-View Perception of Dynamic Scenes <div style="margin: 0px;"> The INRIA MORPHEO research team is working on the perception of moving shapes using multiple camera systems. Such systems allows to recover dense information on shapes and their motions using visual cues. This opens avenues for research investigations on how to model, understand and animate real dynamic shapes using several videos. In this talk I will more particularly focus on recent activities in the team on two fundamental components of the multi-view perception of dynamic scenes that are: (i) the recovery of time-consistent shape models or shape tracki... Gerard Pons-Moll

Perceiving Systems Talk Prof. Yoshinari Kameda 12-03-2014 Producing free viewpoint 3D video from a real soccer game and its user interface for the virtual camera control <p> This talk presents our 3D video production method by which a user can watch a  real game from any free viewpoint. Players in the game are captured by 10 cameras and they are reproduced three dimensionally by billboard based representation in real time. Upon producing the 3D video, we have also worked on good user interface that can enable people move the camera intuitively. As the speaker is also working on wide variety of computer vision to augmented reality, selected recent works will be also introduced briefly.<br /> <br /> Dr. Yoshinari K...

Perceiving Systems Talk Christof Hoppe 11-02-2014 Interactive and Task-driven Multi-view 3D Reconstruction 3D reconstruction from 2D still-images (Structure-from-Motion) has reached maturity and together with new image acquisition devices like Micro Aerial Vehicles (MAV), new interesting application scenarios arise. However, acquiring an image set which is suited for a complete and accurate reconstruction is even for expert users a non-trivial task. To overcome this problem, we propose two different methods. In the first part of the talk, we will present a SfM method that performs sparse reconstruction of 10Mpx still-images and a surface extraction from sparse and noisy 3D point clouds in real-t...

Perceiving Systems IS Colloquium Bernt Schiele 10-02-2014 Towards Visual Scene Understanding - Articulated Pose Estimation and Video Description <p class="p1"> This talk will highlight recent progress on two fronts. First, we will talk about a novel image-conditioned person model that allows for effective articulated pose estimation in realistic scenarios. Second, we describe our work towards activity recognition and the ability to describe video content with natural language. </p> <p class="p2"> Both efforts are part of a longer-term agenda towards visual scene understanding. While visual scene understanding has long been advocated as the "holy grail" of computer vision, we believe it is time to address this cha...

Perceiving Systems IS Colloquium Pascal Fua 13-01-2014 Identity Preserving Multi-People Tracking through Linear Programming <p> In this talk, I will show that, given probabilities of presence of people at various locations in individual time frames, finding the most likely set of trajectories amounts to solving a linear program that depends on very few parameters.<br /> This can be done without requiring appearance information and in real-time, by using the K-Shortest Paths algorithm (KSP). However, this can result in unwarranted identity switches in complex scenes. In such cases, sparse image information can be used within the Linear Programming framework to keep track of people's identities, even when...

Perceiving Systems Talk Alessandra Tosi 18-11-2013 Local metric approach in Gaussian Processes Latent Variables Models <p> Manifold learning techniques attempt to map a high-dimensional space onto a lower-dimensional one. From a mathematical point of view, a manifold is a topological Hausdorff space that is locally Euclidean. From Machine Learning point of view, we can interpret this embedded manifold as the underlying support of the data distribution. When dealing with high dimensional data sets, nonlinear dimensionality reduction methods can provide more faithful data representation than linear ones. However, the local geometrical distortion induced by the nonlinear mapping leads to a loss of informatio...

Perceiving Systems Talk Sven Dickinson 11-11-2013 Perceptual Grouping using Superpixels <p class="p1"> Perceptual grouping played a prominent role in support of early object recognition systems, which typically took an input image and a database of shape models and identified which of the models was visible in the image.  When the database was large, local features were not sufficiently distinctive to prune down the space of models to a manageable number that could be verified.  However, when causally related shape features were grouped, using intermediate-level shape priors, e.g., cotermination, symmetry, and compactness, they formed effective shape indices and all...

Perceiving Systems Talk Padmanabhan Anandan 14-10-2013 Inventing the Future at Microsoft Research India: Our first 8 years <p> T.b.a.</p>

Perceiving Systems Talk Pierre-Yves Laffont 11-10-2013 Exploring and editing the appearance of outdoor scenes <div> The appearance of outdoor scenes changes dramatically with lighting and weather conditions, time of day, and season. Specific conditions, such as the "golden hours" characterized by warm light, can be hard to capture because many scene properties are transient -- they change over time. Despite significant advances in image editing software, common image manipulation tasks such as lighting editing require significant expertise to achieve plausible results.</div> <div>  </div> <div> In this talk, we first explore the appearance of outdoor scenes with an approach base...

Perceiving Systems Talk Neill Campbell 01-10-2013 Inference in highly-connected CRFs This talk presents recent work from CVPR that looks at inference for pairwise CRF models in the highly (or fully) connected case rather than simply a sparse set of neighbours used ubiquitously in many computer vision tasks. Recent work has shown that fully-connected CRFs, where each node is connected to every other node, can be solved very efficiently under the restriction that the pairwise term is a Gaussian kernel over a Euclidean feature space. The method presented generalises this model to allow arbitrary, non-parametric models (which can be learnt from training data and condi...

Perceiving Systems Talk Bei Xiao 23-09-2013 Human perception of material properties in the real world <p> Humans are very good at recognizing objects as well as the materials that they are made of. We can easily tell cheese from butter, silk from linen and snow from ice just by looking. Understanding material perception is important for many real-world applications. For instance, a robot cooking in the kitchen will benefit from the knowledge of material perception when deciding if food is cooked or raw. In this talk, I will present studies that are motivated by two important applications of material perception: online shopping and computer graphics (CG) rendering. First, I will discuss the...

Perceiving Systems Talk Victor Adrian Prisacariu 23-09-2013 Shape Knowledge in Segmentation and Tracking <p> In this talk I will detail methods for simultaneous 2D/3D segmentation, tracking and reconstruction which incorporate high level shape information. I base my work on the assumption that the space of possible 2D object shapes can be either generated by projecting down known rigid 3D shapes or learned from 2D shape examples. I minimise the discrimination between statistical foreground and background appearance models with respect to the parameters governing the shape generative process (the 6 degree-of-freedom 3D pose of the 3D shape or the parameters of the learned space). The foregroun...

Perceiving Systems Talk Alexander Schwing 12-09-2013 Efficient Inference and Learning for Structured Parameterizations/Models Sensors acquire an increasing amount of diverse information posing two challenges. Firstly, how can we efficiently deal with such a big amount of data and secondly, how can we benefit from this diversity? In this talk I will first present an approach to deal with large graphical models. The presented method distributes and parallelizes the computation and memory requirements while preserving convergence and optimality guarantees of existing inference and learning algorithms. I will demonstrate the effectiveness of the approach on stereo reconstruction from high-resolution imagery. In the se...

Perceiving Systems Talk Jamie Shotton 10-09-2013 Depth, You, and the World <p> Consumer level depth cameras such as Kinect have changed the landscape of 3D computer vision.  In this talk we will discuss two approaches that both learn to directly infer correspondences between observed depth image pixels and 3D model points.  These correspondences can then be used to drive an optimization of a generative model to explain the data.  The first approach, the "Vitruvian Manifold", aims to fit an articulated 3D human model to a depth camera image, and extends our original Body Part Recognition algorithm used in Kinect.  It applies a per-pi...

Perceiving Systems Talk Sanja Fidler 09-09-2013 2D and 3D object detection by exploiting segmentation and contextual information <div> Object detection is one of the main challenges of computer vision. In the standard setting, we are given an image and the goal is to place bounding boxes around the objects and recognize their classes. In robotics, estimating additional information such as accurate viewpoint or detailed segmentation is important for planning and interaction. In this talk, I'll approach detection in three scenarios: purely 2D, 3D from 2D and 3D from 3D and show how different types of information can be used to significantly boost the current state-of-the-art in detection.</div> <div>  </div>

Perceiving Systems Talk Raquel Urtasun 09-09-2013 Efficient Algorithms for Semantic Scene Parsing Developing autonomous systems that are able to assist humans in everyday's tasks is one of the grand challenges in modern computer science. Notable examples are personal robotics for the elderly and people with disabilities, as well as autonomous driving systems which can help decrease fatalities caused by traffic accidents. In order to perform tasks such as navigation, recognition and manipulation of objects, these systems should be able to efficiently extract 3D knowledge of their environment.  In this talk, I'll show how Markov random fields provide a great mathematical form...