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A Multi-sensor Traffic Scene Dataset with Omnidirectional Video

A Multi-sensor Traffic Scene Dataset with Omnidirectional Vi...

引用

ieee computer society conference on computer vision and pattern recognition workshops (CVPRW)

作者： Philipp Koschorrek Tommaso Piccini Per Öberg Michael Felsberg Lars Nielsen Rudolf Mester Computer Vision Laboratory Department of Electrical Engineering Linköping University Sweden Vehicular Systems Department of Electrical Engineering Linköping University Sweden Linkopings universitet Linkoping SE

The development of vehicles that perceive their environment, in particular those using computer vision, indispensably requires large databases of sensor recordings obtained from real cars driven in realistic traffic situations. These datasets should be time shaped for enabling synchronization of sensor data from different sources. Furthermore, full surround environment perception requires high frame rates of synchronized omnidirectional video data to prevent information loss at any speeds. This paper describes an experimental setup and software environment for recording such synchronized multi-sensor data streams and storing them in a new open source format. The dataset consists of sequences recorded in various environments from a car equipped with an omnidirectional multi-camera, height sensors, an IMU, a velocity sensor, and a GPS. The software environment for reading these data sets will be provided to the public, together with a collection of long multi-sensor and multi-camera data streams stored in the developed format.

关键词： Cameras Global Positioning System Synchronization Visualization Software computers Robot sensing systems

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Locality-constrained discriminative learning and coding

Locality-constrained discriminative learning and coding

引用

ieee computer society conference on computer vision and pattern recognition workshops (CVPRW)

作者： Shuyang Wang Yun Fu Department of Electrical & Computer Engineering College of Computer & Information Science Northeastern University Boston MA USA

ISBN: (纸本)9781467367608

This paper explores the enhancement by locality constraint to both learning and coding schemes, more specifically, discriminative low-rank dictionary learning and auto-encoder. Previous Fisher discriminative based dictionary learning has led to interesting results by learning more discerning sub-dictionaries. Also, the low-rank regularization term has been introduced to take advantage of the global structure of the data. However, such methods fail to consider data's intrinsic manifold structure. To this end, first, we apply locality constraint on dictionary learning to explore whether the identification capability will be enhanced or not by using the geometric structure information. Moreover, inspired by the recent advances from auto-encoders for learning compact feature spaces, we propose a locality-constrained collaborative auto-encoder (LCAE) for feature extraction. The improvement from applying locality to dictionary learning and auto-encoder is evaluated on several datasets. Experimental results have demonstrated the effectiveness of locality information compared with state-of-the-art methods.

关键词： Dictionaries Training Encoding Yttrium Noise Image reconstruction Feature extraction

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recognition by using an active/space-variant sensor

Recognition by using an active/space-variant sensor

引用

ieee computer society conference on computer vision and pattern recognition workshops (CVPRW)

作者： Tistarelli Laboratory for Integrated Advanced Robotics (LIRA-Lab) DIST-University of Genoa Genoa Italy

The problem of object recognition is addressed. In the literature this task has been generally considered in a "passive" perspective, where everything is static and there is no definite relation between the object and its environment. We propose an "active" approach for object recognition, based on the capability of the observer to move and give a better description of the object under consideration and also to take advantage of the relations between the objects and the environment. This can be accomplished at the task level and at the sensor level. The face recognition problem, based on the face-space approach, is considered to demonstrate the advantage of adopting an active retina to sample the face, build a database and perform the recognition task. By using an active space-variant retina the size of the database is considerably reduced and consequently the processing time for recognition. A comparative experiment using the active and static approach is presented.< >

关键词： Artificial intelligence Machine vision Object recognition

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Localizing parts of faces using a consensus of exemplars

Localizing parts of faces using a consensus of exemplars

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作者： Belhumeur, Peter N. Jacobs, David W. Kriegman, David J. Kumar, Neeraj Kriegman-Belhumeur Vision Technologies United States Columbia University United States University of Maryland College Park United States University of California San Diego United States

ISBN: (纸本)9781457703942

We present a novel approach to localizing parts in images of human faces. The approach combines the output of local detectors with a non-parametric set of global models for the part locations based on over one thousand hand-labeled exemplar images. By assuming that the global models generate the part locations as hidden variables, we derive a Bayesian objective function. This function is optimized using a consensus of models for these hidden variables. The resulting localizer handles a much wider range of expression, pose, lighting and occlusion than prior ones. We show excellent performance on a new dataset gathered from the internet and show that our localizer achieves state-of-the-art performance on the less challenging BioID dataset. © 2011 ieee.

关键词： computers

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Occluding contour detection using affine invariants and purposive viewpoint control

Occluding contour detection using affine invariants and purp...

引用

ieee computer society conference on computer vision and pattern recognition workshops (CVPRW)

作者： Kutulakos Dyer Computer Science Department University of Wisconsin Madison WI USA

We present an approach for identifying the occluding contour and determining its sidedness using an active (i.e., moving) observer. It is based on the non-stationarity property of the visible rim: When the observer's viewpoint is changed, the visible rim is a collection of curves that "slide," rigidly or non-rigidly over the surface. We show that the absenter can deterministically choose three views on the tangent plane of selected surface points to distinguish such curves from stationary surface curves (i.e., surface markings). Our approach demonstrates that the occluding contour can be identified directly, i.e., without first computing surface shape (distance and curvature).< >

关键词： Image motion analysis Machine vision Computational geometry

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CTREC: C-arm tracking and reconstruction using elliptic curves

CTREC: C-arm tracking and reconstruction using elliptic curv...

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ieee computer society conference on computer vision and pattern recognition workshops (CVPRW)

作者： Gouthami Chintalapani Ameet K. Jain David H. Burkhardt Jerry L. Prince Gabor Fichtinger Johns Hopkins University USA Philips Research North America USA Haverford College USA Queen's University Canada

C-arm fluoroscopy is ubiquitous in contemporary surgery, but it lacks the ability to accurately reconstruct three-dimensional information, attributable to the difficulty in obtaining the pose of X-ray images in 3D space. We propose a unified mathematical framework to address the issues of intra-operative pose estimation, correspondence and reconstruction, using simple elliptic curves. In contrast to other fiducial-based tracking methods, our method uses a single ellipse to constrain 5 out of 6 degrees of freedom of C-arm pose, along with randomly distributed unknown points in the imaging volume (either naturally present or induced by randomly placed beads or other markers in the image space) from two images/views to completely recover the Carm pose. Preliminary phantom experiments indicate an average C-arm tracking accuracy of 0.51. and 0.12. STD. The method appears to be sufficiently accurate and appealing for many clinical applications, since it uses a simple elliptic fiducial coupled with patient information and has very minimal interference with the workspace.

关键词： Elliptic curves Image reconstruction Calibration Optical imaging Nonlinear distortion computer vision Optical distortion Image segmentation North America Educational institutions

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Global temporal registration of multiple non-rigid surface sequences

Global temporal registration of multiple non-rigid surface s...

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作者： Huang, Peng Budd, Chris Hilton, Adrian Centre for Vision Speech Signal Processing University of Surrey Guildford GU2 7XH United Kingdom

ISBN: (纸本)9781457703942

In this paper we consider the problem of aligning multiple non-rigid surface mesh sequences into a single temporally consistent representation of the shape and motion. A global alignment graph structure is introduced which uses shape similarity to identify frames for inter-sequence registration. Graph optimisation is performed to minimise the total non-rigid deformation required to register the input sequences into a common structure. The resulting global alignment ensures that all input sequences are resampled with a common mesh structure which preserves the shape and temporal correspondence. Results demonstrate temporally consistent representation of several public databases of mesh sequences for multiple people performing a variety of motions with loose clothing and hair. © 2011 ieee.

关键词： Mesh generation

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Automated fast recognition and location of arbitrarily shaped objects by image morphology.

Automated fast recognition and location of arbitrarily shape...

引用

Proceedings - CVPR '88: computer society conference on computer vision and pattern recognition

作者： Shih, Frank Y. Mitchell, O.Robert New Jersey Inst of Technology Newark NJ USA

ISBN: (纸本)0818608625

Morphological operations are used for segmentation, feature generation, and location extraction. A recursive adaptive thresholding algorithm transforms a gray-level image into a set of multiple level regions of objects. A distance transformation algorithm then is used to transform a binary image into the minimum distance from each object point to the object's boundary. This algorithm uses a morphological erosion with a large structuring element which may correspond to Euclidean, city-block, or chessboard distance measures. For rotation-invariance and precision measurements, the Euclidean distance should be chosen. The large Euclidean structuring element can be decomposed into the maximum of recursive dilations with multiple small structuring components, which allows the easy implementation of this algorithm. A shape library database with hierarchical features is automatically generated. The features extracted are the shape number and the skeletal local-maximum points radii and coordinates. Object recognition is achieved by comparing the shape number and the hierarchical radii. Object location is detected by a hierarchical morphological bandpass filter.

关键词： pattern recognition systems

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WiCV 2019: The Sixth Women In computer vision Workshop

WiCV 2019: The Sixth Women In Computer Vision Workshop

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ieee computer society conference on computer vision and pattern recognition workshops (CVPRW)

作者： Irene Amerini Elena Balashova Sayna Ebrahimi Kathryn Leonard Arsha Nagrani Amaia Salvador University of Florence Princeton University UC Berkeley Occidental College University of Oxford Universitat Politcnica de Catalunya

ISBN: (数字)9781728125060

ISBN: (纸本)9781728125077

In this paper we present the Women in computer vision Workshop - WiCV 2019, organized in conjunction with CVPR 2019. This event is meant for increasing the visibility and inclusion of women researchers in computer vision field. computer vision and machine learning have made incredible progress over the past years, but the number of female researchers is still low both in the academia and in the industry. WiCV is organized especially for this reason: to raise visibility of female researchers, to increase collaborations between them, and to provide mentorship to female junior researchers in the field. In this paper, we present a report of trends over the past years, along with a summary of statistics regarding presenters, attendees, and sponsorship for the current workshop.

关键词： conferences computer vision Machine learning Engineering profession Facebook Buildings

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作者： Smith, David L. Field, Jacqueline Learned-Miller, Erik Department of Computer Science University of Massachusetts Amherst Amherst MA 01003 United States

ISBN: (纸本)9781457703942

The recognition of text in everyday scenes is made difficult by viewing conditions, unusual fonts, and lack of linguistic context. Most methods integrate a priori appearance information and some sort of hard or soft constraint on the allowable strings. Weinman and Learned-Miller [14] showed that the similarity among characters, as a supplement to the appearance of the characters with respect to a model, could be used to improve scene text recognition. In this work, we make further improvements to scene text recognition by taking a novel approach to the incorporation of similarity. In particular, we train a similarity expert that learns to classify each pair of characters as equivalent or not. After removing logical inconsistencies in an equivalence graph, we formulate the search for the maximum likelihood interpretation of a sign as an integer program. We incorporate the equivalence information as constraints in the integer program and build an optimization criterion out of appearance features and character bigrams. Finally, we take the optimal solution from the integer program, and compare all "nearby" solutions using a probability model for strings derived from search engine queries. We demonstrate word error reductions of more than 30% relative to previous methods on the same data set. © 2011 ieee.

关键词： Search engines

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