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Towards optimal vlad for human action recognition from still images

Towards optimal vlad for human action recognition from still...

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international conference on Acoustics, Speech, and Signal processing (ICASSP)

作者： Lei Zhang Xiantong Zhen Jiqing Han College of Information and Communication Engineering Harbin Engineering University Harbin PRC University of Western Ontario London ON Canada School of Computer Science and Technology Harbin Institute of Technology Harbin PRC

ISBN: (纸本)9781479999897

Human action recognition from still image has recently drawn increasing attention in human behavior analysis vision and also poses great challenges due to the huge inter ambiguity and intra variability. Vector of locally aggregated descriptors (VLAD) has achieved state-of-the-art performance in many image classification tasks based on local features. The great success of VLAD is largely due to its high descriptive ability and computational efficiency. In this paper, towards optimal VLAD representations for human action recognition from still images, we improve VLAD by tackling two important issues in VLAD including empty cavity and assignment ambiguity. The empty cavity issue severely compromises the performance of VLAD and has long been overlooked. We investigate the empty cavity and provide an effective solution to deal with it, which largely improves the performance of VLAD; we propose middle level assignments to conquer the assignment ambiguity, which are more reliable and can provide more useful information for realistic activity. We have conducted extensive experiments on two widely-used benchmarks to validate the proposed method for human action recognition from still images. Our method produces competitive performance with state-of-the-art algorithms.

关键词： Cavity resonators Kernel image recognition Standards Reliability Benchmark testing Weight measurement

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Height detection in smart baby weighing system using machine vision

Height detection in smart baby weighing system using machine...

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2016 international conference on Automotive Engineering,Mechanical and Electrical Engineering(AEMEE 2016)

作者： Qiang Fang Huanrong Tang Xiangtan University

At present, the height of a baby is detected manually by a nurse. In order to realise rapid non-destructive testing for the detection of a baby's height and weight, a module was established to detect the height of baby based on machine vision in a smart baby weighing system. This paper proposed a fast detection method for finding a baby's height using the Grab Cut segmentation algorithm, based on the image captured by a monocular camera in a smart baby weighing system. First, a baby was marked by preprocessing and a body detector. Second, by accurately extracting the feature points of the top of the head and the feet, the real height of the baby is calculated accurately using the theory of the Grab Cut segmentation algorithm. The test results proved that the method has obtained the precision of the manual method at present and been adaptive to the angle of camera and baby moving posture. The simple and efficient structure of the detecting system ensures its application.

关键词： Height Detection Smart Baby Weighing System Monocular Machine vision image processing

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Monocular, Real-Time Surface Reconstruction Using Dynamic Level of Detail

Monocular, Real-Time Surface Reconstruction Using Dynamic Le...

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international conference on 3D Imaging, Modeling, processing, Visualization and Transmission (3DIMPVT)

作者： Jacek Zienkiewicz Akis Tsiotsios Andrew Davison Stefan Leutenegger Imperial College London Dyson Robotics Lab London UK

ISBN: (纸本)9781509054084

We present a scalable, real-time capable method for robust surface reconstruction that explicitly handles multiple scales. As a monocular camera browses a scene, our algorithm processes images as they arrive and incrementally builds a detailed surface *** most of the existing reconstruction approaches rely on volumetric or point-cloud representations of the environment, we perform depth-map and colour fusion directly into a multi-resolution triangular mesh that can be adaptively tessellated using the concept of Dynamic Level of Detail. Our method relies on least-squares optimisation, which enables a probabilistically sound and principled formulation of the fusion *** demonstrate that our method is capable of obtaining high quality, close-up reconstruction, as well as capturing overall scene geometry, while being memory and computationally efficient.

关键词： Cameras image reconstruction Surface reconstruction Real-time systems Three-dimensional displays Rendering (computer graphics) Heuristic algorithms

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Pushing the limit of non-rigid structure-from-motion by shape clustering

Pushing the limit of non-rigid structure-from-motion by shap...

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international conference on Acoustics, Speech, and Signal processing (ICASSP)

作者： Huizhong Deng Yuchao Dai College of Engineering and Computer Science Australian National University Australia

ISBN: (纸本)9781479999897

Recovering both camera motions and non-rigid 3D shapes from 2D feature tracks is a challenging problem in computer vision. Long-term, complex non-rigid shape variations in real world videos further increase the difficulty for Non-rigid structure-from-motion (NRSfM). Furthermore, there does not exist a criterion to characterize the possibility in recovering the non-rigid shapes and camera motions (i.e., how easy or how difficult the problem could be). In this paper, we first present an analysis to the "reconstructability" measure for NRSfM, where we show that 3D shape complexity and camera motion complexity can be used to index the re-constructability. We propose an iterative shape clustering based method to NRSfM, which alternates between 3D shape clustering and 3D shape reconstruction. Thus, the global reconstructability has been improved and better reconstruction can be achieved. Experimental results on long-term, complex non-rigid motion sequences show that our method outperforms the current state-of-the-art methods by a margin.

关键词： Shape Three-dimensional displays Cameras image reconstruction Complexity theory Trajectory Iterative methods

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Radiometric Scene Decomposition: Scene Reflectance, Illumination, and Geometry from RGB-D images

Radiometric Scene Decomposition: Scene Reflectance, Illumina...

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international conference on 3D Imaging, Modeling, processing, Visualization and Transmission (3DIMPVT)

作者： Stephen Lombardi Ko Nishino Department of Computer Science Drexel University

ISBN: (纸本)9781509054084

Recovering the radiometric properties of a scene (i.e., the reflectance, illumination, and geometry) is a long-sought ability of computer vision that can provide invaluable information for a wide range of applications. Deciphering the radiometric ingredients from the appearance of a real-world scene, as opposed to a single isolated object, is particularly challenging as it generally consists of various objects with different material compositions exhibiting complex reflectance and light interactions that are also part of the illumination. We introduce the first method for radiometric decomposition of real-world scenes that handles those intricacies. We use RGB-D images to bootstrap geometry recovery and simultaneously recover the complex reflectance and natural illumination while refining the noisy initial geometry and segmenting the scene into different material regions. Most important, we handle real-world scenes consisting of multiple objects of unknown materials, which necessitates the modeling of spatially-varying complex reflectance, natural illumination, texture, interreflection and shadows. We systematically evaluate the effectiveness of our method on synthetic scenes and demonstrate its application to real-world scenes. The results show that rich radiometric information can be recovered from RGB-D images and demonstrate a new role RGB-D sensors can play for general scene understanding tasks.

关键词： Geometry Lighting Radiometry Brain modeling image segmentation Computational modeling Estimation

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HS-Nets: Estimating Human Body Shape from Silhouettes with Convolutional Neural Networks

HS-Nets: Estimating Human Body Shape from Silhouettes with C...

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international conference on 3D Imaging, Modeling, processing, Visualization and Transmission (3DIMPVT)

作者： Endri Dibra Himanshu Jain Cengiz Öztireli Remo Ziegler Markus Gross Department of Computer Science ETH Zürich Vizrt

We represent human body shape estimation from binary silhouettes or shaded images as a regression problem, and describe a novel method to tackle it using CNNs. Utilizing a parametric body model, we train CNNs to learn a global mapping from the input to shape parameters used to reconstruct the shapes of people, in neutral poses, with the application of garment fitting in mind. This results in an accurate, robust and automatic system, orders of magnitude faster than methods we compare to, enabling interactive applications. In addition, we show how to combine silhouettes from two views to improve prediction over a single view. The method is extensively evaluated on thousands of synthetic shapes and real data and compared to state of-art approaches, clearly outperforming methods based on global fitting and strongly competing with more expensive local fitting based ones.

关键词： Shape Three-dimensional displays Estimation Biological system modeling Clothing image reconstruction Robustness

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Automatic detection of neovascularization on optic disk region with feature extraction and support vector machine

Automatic detection of neovascularization on optic disk regi...

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Annual international conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Shuang Yu Di Xiao Yogesan Kanagasingam Australian e-Health Research Centre Commonwealth Scientific and Industrial Research Organization (CSIRO)

Neovascularization (NV) is a definitive indicator for the onset of Proliferative Diabetic Retinopathy (PDR). The new vessels are fragile and prone to bleed, leading to high risk of sudden vision loss. Automatic detection of NV is an important task in automatic Diabetic Retinopathy (DR) screening as a consequence of the unmet requirement between the growing number of DR patients and limited number of ophthalmologists. This paper focuses on the computer aided detection of neovascularization in the optic disk region. We propose a novel image processing approach that involves vessel segmentation using multi-level Gabor filtering, feature extraction from vessel related features and texture features, and image classification based on machine learning. 21 features were extracted from each NVD image. The extracted features were trained and tested on 66 retinal images, which contains 16 NVD and 50 normal images, and achieved an sensitivity of 15/16 and specificity of 47/50.

关键词： Feature extraction Optical imaging Support vector machines Training Retina Optical filters image segmentation

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Towards a smart selection of resources for low-energy multimedia processing

Towards a smart selection of resources for low-energy multim...

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international conference on Cloud Technologies and Applications (CloudTech)

作者： Sidi Ahmed Mahmoudi Faculty of Engineering University of Mons Belgium

ISBN: (纸本)9781467388955

Today, one can find images and videos everywhere, they can come from cameras, mobile phones or from other devices. These images and videos are used to illustrate different objects in a large number of situations (airports, hospitals, public areas, sport events, etc.). This makes the task of processing images and videos a necessary tool that can be used for various domains related to computer vision. The performance of these algorithms have been so reduced due to their high intensive computation and energy consumption. In this work, we propose a new framework that allows users to select in a smart and efficient way the computing units (CPU or/and GPU) in case of processing single image, multiple images, multiple videos or single video in real time. This framework enables to affect the CPU or/and GPU units for calculation depending on the type of media to process and the algorithm complexity. The framework provides several image and video functions on GPU, such as silhouette extraction, points of interest extraction, edges detection, sparse and dense optical flow estimation. These functions are exploited in different applications such as vertebra segmentation in X-ray and MR images, gaze estimation, event detection and localization in real time. Experimental results have been obtained by applying the framework for different use case applications showing a speedup ranging from 5 to 116×, by comparison with sequential CPU implementations. In addition to these performance, the parallel and heterogeneous implementation offered lower power consumption as a result for the fast treatment.

关键词： Biomedical imaging Performance evaluation Estimation Cameras image edge detection Hardware Graphics processing units

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Robust ground plane detection and tracking in stereo sequences using camera orientation

Robust ground plane detection and tracking in stereo sequenc...

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international conference on System Theory, Control, and Computing (ICSTCC)

作者： Paul Herghelegiu Adrian Burlacu Simona Caraiman Faculty of Automatic Control and Computer Engineering Technical University “Gheorghe Asachi” Iasi Romania

ISBN: (纸本)9781509027217

The research on assisting visually impaired people to navigate in unknown environments commonly employs image processing or computer vision techniques. One key element that needs to be identified in the surrounding environment of a blind user is the ground plane. Its accurate detection is highly important because the user is able to move freely in that area. An assistive device should primarily assist the user in avoiding the obstacles that lie on the ground surface. The images that will be further processed are usually acquired using depth acquisition devices worn by the user. Therefore, in contrast with automotive or robotics applications, which also heavily rely on ground plane extraction for obstacle detection, the camera orientation has more degrees of freedom. This leads to the requirement of designing more complex solutions for the ground plane detection in the case of assistive systems for the visually impaired. In this paper we introduce an algorithm to detect the ground plane taking into consideration the orientation of the camera, namely its pitch and roll. The proposed algorithm is based on an efficient processing of the v-disparity map associated to each frame. A two-step decision making approach to determine the most suited area that corresponds to the ground plane is described. Experimental results with synthetic datasets are provided to prove the efficiency and robustness of the proposed approach.

关键词： Cameras Three-dimensional displays Transforms image segmentation Navigation Surface treatment

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24.1 A 0.6V 8mW 3D vision processor for a navigation device for the visually impaired

24.1 A 0.6V 8mW 3D vision processor for a navigation device ...

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IEEE international conference on Solid-State Circuits (ISSCC)

作者： Dongsuk Jeon Nathan Ickes Priyanka Raina Hsueh-Cheng Wang Daniela Rus Anantha Chandrakasan Massachusetts Institute of Technology Cambridge MA Seoul National University Suwon Korea

3D imaging devices, such as stereo and time-of-flight (ToF) cameras, measure distances to the observed points and generate a depth image where each pixel represents a distance to the corresponding location. The depth image can be converted into a 3D point cloud using simple linear operations. This spatial information provides detailed understanding of the environment and is currently employed in a wide range of applications such as human motion capture [1]. However, its distinct characteristics from conventional color images necessitate different approaches to efficiently extract useful information. This paper describes a low-power vision processor for processing such 3D image data. The processor achieves high energy-efficiency through a parallelized reconfigurable architecture and hardware-oriented algorithmic optimizations. The processor will be used as a part of a navigation device for the visually impaired (Fig. 24.1.1). This handheld or body-worn device is designed to detect safe areas and obstacles and provide feedback to a user. We employ a ToF camera as the main sensor in this system since it has a small form factor and requires relatively low computational complexity [2].

关键词： Three-dimensional displays Navigation Cameras computer architecture Surface treatment Out of order Optimization

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