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Cascaded Sequential Attention for Object recognition with Informative Local Descriptors and Q-learning of Grouping Strategies

Cascaded Sequential Attention for Object Recognition with In...

引用

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

作者： L. Paletta G. Fritz C. Seifert Joanneum Research Forschungsgesellschaft mbH Institute of Digital Image Processing Graz Austria

The contribution of this work is to provide a three-stage architecture for sequential attention to provide a system being capable of sensorimotor object detection in real world environments. The first processing stage provides selected foci of interest in the image based on the extraction of information theoretic saliency of local image descriptors (i-SIFT). The second stage investigates the information in the local attention window using a codebook matcher, providing local weak hypotheses about the identity of the object under investigation. The third stage then proposes a shift of attention to a next attention window. The working hypothesis is to expect a better discrimination from the integration of both the individual local FOA patterns and the geometric relation between them, providing a model of more global information representation, and feeding into a recognition state in the Markov Decision Process (MDP). A reinforcement learner (Q-learner) performs then explorative search on useful actions, i.e., shifts of attention, towards locations of salient information, developing a strategy of useful action sequences being directed in state space towards the optimization of discrimination by information maximization. The method is evaluated in experiments using the COIL-20 database (indoor imagery) and the TSG-20 database (outdoor imagery) to demonstrate efficient performance in object detection tasks, proving the method being more accurate and computationally much less expensive than standard SIFT based recognition.

关键词： Object recognition Layout Humans Object detection Data mining pattern recognition Image databases Psychology Encoding Sampling methods

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Groupwise Morphometric Analysis based on Morphological Appearance Manifold

Groupwise Morphometric Analysis based on Morphological Appea...

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ieee computer society conference on computer vision and pattern recognition workshops

作者： Nai-Xiang Lian Christos Davatzikos Department of Radiology University of Pennsylvania

ISBN: (纸本)9781424439942

The field of computational anatomy has developed rigorous frameworks for analyzing anatomical shape, based on diffeomorphic transformations of a template. However, differences in algorithms used for template warping, in regularization parameters, and in the template itself, lead to different representations of the same anatomy. Variations of these parameters are considered as confounding factors as they give rise to non-unique representation. Recently, extensions of the conventional computational anatomy framework to account for such confounding variations have shown that learning the equivalence class derived from the multitude of representations can lead to improved and more stable morphological descriptors. Herein, we follow that approach, estimating the morphological appearance manifold obtained by varying parameters of the template warping procedure. Our approach parallels work in the computer vision field, in which variations lighting, pose and other parameters leads to image appearance manifolds representing the exact same figure in different ways. The proposed framework is then used for groupwise registration and statistical analysis of biomedical images, by employing a minimum variance criterion on selected complete morphological descriptor to perform manifold-constrained optimization, i.e. to traverse each individual's morphological appearance manifold until group variance is minimal. Effectively, this process removes the aforementioned confounding effects and potentially leads to morphological representations reflecting purely biological variations, instead of variations introduced by modeling assumptions and parameter settings. The nonlinearity of a morphological appearance manifold is treated via local approximations of the manifold via PCA.

关键词： Anatomy Shape Biological system modeling Principal component analysis Biology computing Biomedical measurements Smoothing methods Radiology computer vision Statistical analysis

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Longitudinal face modeling via Temporal Deep Restricted Boltzmann Machines

Longitudinal face modeling via Temporal Deep Restricted Bolt...

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2016 ieee conference on computer vision and pattern recognition, CVPR 2016

作者： Duong, Chi Nhan Luu, Khoa Quach, Kha Gia Bui, Tien D. Computer Science and Software Engineering Concordia University MontréalQC Canada CyLab. Biometrics Center Department of Electrical and Computer Engineering Carnegie Mellon University PittsburghPA United States

ISBN: (纸本)9781467388511

Modeling the face aging process is a challenging task due to large and non-linear variations present in different stages of face development. This paper presents a deep model approach for face age progression that can efficiently capture the non-linear aging process and automatically synthesize a series of age-progressed faces in various age ranges. In this approach, we first decompose the longterm age progress into a sequence of short-term changes and model it as a face sequence. The Temporal Deep Restricted Boltzmann Machines based age progression model together with the prototype faces are then constructed to learn the aging transformation between faces in the sequence. In addition, to enhance the wrinkles of faces in the later age ranges, the wrinkle models are further constructed using Restricted Boltzmann Machines to capture their variations in different facial regions. The geometry constraints are also taken into account in the last step for more consistent age-progressed results. The proposed approach is evaluated using various face aging databases, i.e. FG-NET, Cross-Age Celebrity Dataset (CACD) and MORPH, and our collected large-scale aging database named AginG Faces in the Wild (AGFW). In addition, when ground-truth age is not available for input image, our proposed system is able to automatically estimate the age of the input face before aging process is employed.

关键词： computer vision

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On the utility of extended fingerprint features: A study on pores

On the utility of extended fingerprint features: A study on ...

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

作者： Qijun Zhao Anil K. Jain Department of Computer Science and Engineering Michigan State University East Lansing MI USA

Extended fingerprint features are routinely used by latent examiners in forensic applications. They are now being considered for inclusion in automatic fingerprint identification systems (AFIS), particularly with the adoption of 1000ppi resolution in the Next Generation Identification (NGI) system. Earlier studies on this topic suffered from two limitations: (i) experiments were based on live scan images that are generally of good quality and contain smaller intra-class variations compared to ink images and (ii) the baseline minutiae matcher used to measure the additive value of extended features was not a state-of-the-art matcher. In this paper, we study the utility of pores, one of the most prevalent extended fingerprint features, on rolled ink fingerprint images at both 500ppi and 1000ppi resolution in the NIST SD30 database. The results show that the fingerprint image quality significantly affects the automatic extraction and matching accuracy of pores. Furthermore, the contribution of pores to the overall fingerprint recognition accuracy is miniscule when a COTS matcher is used for 500ppi rolled ink fingerprint images. The fusion between pore matcher and COTS minutiae matcher is a bit more effective on 1000ppi good quality rolled ink fingerprint images. We believe that these results will be useful in the design of next generation AFIS.

关键词： Fingerprint recognition Image matching Ink Forensics Image databases Spatial databases Bifurcation Image resolution NIST Law enforcement

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Hardware implementation of a binary neural image processor

Hardware implementation of a binary neural image processor

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Proceedings of the 5th International conference on Image Processing and its Applications

作者： Kennedy, J.V. Austin, J. Cass, B. Univ of York United Kingdom

This paper presents the work that has resulted in the SAT processor;a dedicated hardware implementation of a binary neural image processor. The SAT processor is aimed specifically at supporting the ADAM algorithm and is currently being integrated into a new version of the C-NNAP parallel image processor. The SAT processor performs binary matrix multiplications, a task that is computationally complex for a CPU with a standard instruction set. It can perform the matrix multiplication and thresholding between 100 and 200 times faster than the DSP32C that uses an in-house produced dedicated coprocessor. This speed-up will allow the SAT to process images of up to 220 × 220 pixels at 25-Hz frame rates.

关键词： computer hardware

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Location-based augmented reality on mobile phones

Location-based augmented reality on mobile phones

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

作者： Rémi Paucher Matthew Turk Computer Science Department University of California Santa Barbara USA

The computational capability of mobile phones has been rapidly increasing, to the point where augmented reality has become feasible on cell phones. We present an approach to indoor localization and pose estimation in order to support augmented reality applications on a mobile phone platform. Using the embedded camera, the application localizes the device in a familiar environment and determines its orientation. Once the 6 DOF pose is determined, 3D virtual objects from a database can be projected into the image and displayed for the mobile user. Off-line data acquisition consists of acquiring images at different locations in the environment. The online pose estimation is done by a feature-based matching between the cell phone image and an image selected from the precomputed database using the phone's sensors (accelerometer and magnetometer). The application enables the user both to visualize virtual objects in the camera image and to localize the user in a familiar environment. We describe in detail the process of building the database and the pose estimation algorithm used on the mobile phone. We evaluate the algorithm performance as well as its accuracy in terms of reprojection distance of the 3D virtual objects in the cell phone image.

关键词： Augmented reality Mobile handsets Cellular phones Image databases Cameras Spatial databases Visual databases Object oriented databases Data acquisition Image sensors

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Randomized decision forests for static and dynamic hand shape classification

Randomized decision forests for static and dynamic hand shap...

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

作者： Cem Keskin Furkan Kiraç Yunus Emre Kara Laie Akarun Computer Engineering Department Boğaziçi University Istanbul Turkey

This paper proposes a novel algorithm to perform hand shape classification using depth sensors, without relying on color or temporal information. Hence, the system is independent of lighting conditions and does not need a hand registration step. The proposed method uses randomized classification forests (RDF) to assign class labels to each pixel on a depth image, and the final class label is determined by voting. This method is shown to achieve 97.8% success rate on an American Sign Language (ASL) dataset consisting of 65k images collected from five subjects with a depth sensor. More experiments are conducted on a subset of the ChaLearn Gesture Dataset, consisting of a lexicon with static and dynamic hand shapes. The hands are found using motion cues and cropped using depth information, with a precision rate of 87.88% when there are multiple gestures, and 94.35% when there is a single gesture in the sample. The hand shape classification success rate is 94.74% on a small subset of nine gestures corresponding to a single lexicon. The success rate is 74.3% for the leave-one-subject-out scheme, and 67.14% when training is conducted on an external dataset consisting of the same gestures. The method runs on the CPU in real-time, and is capable of running on the GPU for further increase in speed.

关键词： Shape Training Sensors Accuracy Vegetation Image segmentation Decision trees

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Salient coding for image classification

Salient coding for image classification

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作者： Huang, Yongzhen Huang, Kaiqi Yu, Yinan Tan, Tieniu National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781457703942

The codebook based (bag-of-words) model is a widely applied model for image classification. We analyze recent coding strategies in this model, and find that saliency is the fundamental characteristic of coding. The saliency in coding means that if a visual code is much closer to a descriptor than other codes, it will obtain a very strong response. The salient representation under maximum pooling operation leads to the state-of-the-art performance on many databases and competitions. However, most current coding schemes do not recognize the role of salient representation, so that they may lead to large deviations in representing local descriptors. In this paper, we propose "salient coding", which employs the ratio between descriptors' nearest code and other codes to describe descriptors. This approach can guarantee salient representation without deviations. We study salient coding on two sets of image classification databases (15-Scenes and PASCAL VOC2007). The experimental results demonstrate that our approach outperforms all other coding methods in image classification. © 2011 ieee.

关键词： Image classification

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TVParser: An automatic TV video parsing method

TVParser: An automatic TV video parsing method

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作者： Liang, Chao Xu, Changsheng Cheng, Jian Lu, Hanqing National Lab of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing 100190 China China-Singapore Institute of Digital Media Singapore 119615 Singapore

ISBN: (纸本)9781457703942

In this paper, we propose an automatic approach to simultaneously name faces and discover scenes in TV shows. We follow the multi-modal idea of utilizing script to assist video content understanding, but without using timestamp (provided by script-subtitles alignment) as the connection. Instead, the temporal relation between faces in the video and names in the script is investigated in our approach, and an global optimal video-script alignment is inferred according to the character correspondence. The contribution of this paper is two-fold: (1) we propose a generative model, named TVParser, to depict the temporal character correspondence between video and script, from which face-name relationship can be automatically learned as a model parameter, and meanwhile, video scene structure can be effectively inferred as a hidden state sequence;(2) we find fast algorithms to accelerate both model parameter learning and state inference, resulting in an efficient and global optimal alignment. We conduct extensive comparative experiments on popular TV series and report comparable and even superior performance over existing methods. © 2011 ieee.

关键词： Alignment

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3D Face recognition Using Two Views Face Modeling and Labeling

3D Face Recognition Using Two Views Face Modeling and Labeli...

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

作者： Yi Sun Lijun Yin Computer Science Department State University of New York Binghamton Binghamton NY USA

The ability to distinguish different people by using 3D facial information is an active research problem being undertaken by the face recognition community. In this paper, we propose to use a generic model to label the 3D facial features. This approach relies on our realistic face modeling technique, by which the individual face model is created using a generic model and two views of a face. In the individualized model, we label the face features by their maximum and minimum curvatures. Among the labeled features, the "good features" are selected by using a Genetic Algorithm based approach. The feature space is then formed by using these new 3D shape descriptors, and each individual face is classified according to its feature space correlation. We applied 72 individual models for the test. The experimental results show that the shape information obtained from the 3D individualized model can be used to classify and identify individual facial surfaces. The rank-four correct recognition rate is about 92%. The 3D individualized model provides consistent and sufficient details to represent individual faces while using a much more simpli?ed representation than the range data models. This work provides the possibility to reduce the complexity of 3D data processing, and is feasible for real applications such as in a non-cooperative imaging circumstance or in the situation when range data using 3D scanners are not possible to acquire.

关键词： Face recognition Labeling Shape Facial animation Data processing Sun computer science Facial features Genetic algorithms Testing

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