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https://www.readbyqxmd.com/read/28212106/view-based-3-d-model-retrieval-a-benchmark
#1
An-An Liu, Wei-Zhi Nie, Yue Gao, Yu-Ting Su
View-based 3-D model retrieval is one of the most important techniques in numerous applications of computer vision. While many methods have been proposed in recent years, to the best of our knowledge, there is no benchmark to evaluate the state-of-the-art methods. To tackle this problem, we systematically investigate and evaluate the related methods by: 1) proposing a clique graph-based method and 2) reimplementing six representative methods. Moreover, we concurrently evaluate both hand-crafted visual features and deep features on four popular datasets (NTU60, NTU216, PSB, and ETH) and one challenging real-world multiview model dataset (MV-RED) prepared by our group with various evaluation criteria to understand how these algorithms perform...
February 15, 2017: IEEE Transactions on Cybernetics
https://www.readbyqxmd.com/read/28212086/salient-object-detection-via-multiple-instance-learning
#2
Fang Huang, Qi Jinqing, Huchuan Lu, Lihe Zhang, Xiang Ruan
Object proposals are a series of candidate segments containing objects of interest, which are taken as preprocessing and widely applied in various vision tasks. However, most of existing saliency approaches only utilize the proposals to compute a location prior. In this paper, we naturally take the proposals as the bags of instances of multiple instance learning (MIL), where the instances are the superpixels contained in the proposals, and formulate saliency detection problem as a MIL task (i.e., predict the labels of instances using the classifier in the MIL framework)...
February 15, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28212077/robust-guided-image-filtering-using-nonconvex-potentials
#3
Bumsub Ham, Minsu Cho, Jean Ponce
Filtering images using a guidance signal, a process called guided or joint image filtering, has been used in various tasks in computer vision and computational photography, particularly for noise reduction and joint upsampling. This uses an additional guidance signal as a structure prior, and transfers the structure of the guidance signal to an input image, restoring noisy or altered image structure. The main drawbacks of such a data-dependent framework are that it does not consider structural differences between guidance and input images, and that it is not robust to outliers...
February 14, 2017: IEEE Transactions on Pattern Analysis and Machine Intelligence
https://www.readbyqxmd.com/read/28210404/infraorbital-nerve-decompression-for-infraorbital-neuralgia-causalgia-following-blowout-orbital-fractures-a-case-series
#4
Bijan Beigi, Mazda Beigi, Nuwan Niyadurupola, Manuel Saldana, Nabil El-Hindy, Deepak Gupta
The purpose of this study was to present the management of a series of patients referred with infraorbital nerve paraesthesia that developed after insignificant orbital floor fracture without diplopia or exophthalmos, and that did not require initial surgical repair. This is a retrospective interventional case series. The main outcome and measures were assessment of preoperative symptoms including neuralgia and sensory symptoms; review of periorbital computed tomography (CT) scans; and assessment of postoperative effects of surgery for infraorbital nerve decompression...
March 2017: Craniomaxillofacial Trauma & Reconstruction
https://www.readbyqxmd.com/read/28210185/neoplastic-leptomeningeal-disease-masquerading-as-central-serous-retinopathy-a-case-report
#5
Ibrahim Elaraoud, Hanif J Suleman, Peter Cikatricis, Helen Palmer
A 69-year-old man became aware of people's speech being out of synch with their lip movements alongside persistent headaches, both of which progressively worsened. A few weeks later, he developed progressive and painless visual loss in one eye. Initial neurological evaluation, inflammatory markers and head computed tomography scan were normal. Ophthalmological examination and OCT scan revealed right macular subretinal fluid with choroidal indentation, which prompted urgent further investigations including head MRI revealing extensive leptomeningeal disease...
July 2016: Saudi Journal of Ophthalmology: Official Journal of the Saudi Ophthalmological Society
https://www.readbyqxmd.com/read/28209965/high-amplitude-electrical-stimulation-can-reduce-elicited-neuronal-activity-in-visual-prosthesis
#6
Alejandro Barriga-Rivera, Tianruo Guo, Chih-Yu Yang, Amr Al Abed, Socrates Dokos, Nigel H Lovell, John W Morley, Gregg J Suaning
Retinal electrostimulation is promising a successful therapy to restore functional vision. However, a narrow stimulating current range exists between retinal neuron excitation and inhibition which may lead to misperformance of visual prostheses. As the conveyance of representation of complex visual scenes may require neighbouring electrodes to be activated simultaneously, electric field summation may contribute to reach this inhibitory threshold. This study used three approaches to assess the implications of relatively high stimulating conditions in visual prostheses: (1) in vivo, using a suprachoroidal prosthesis implanted in a feline model, (2) in vitro through electrostimulation of murine retinal preparations, and (3) in silico by computing the response of a population of retinal ganglion cells...
February 17, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28208671/a-passive-learning-sensor-architecture-for-multimodal-image-labeling-an-application-for-social-robots
#7
Marco A Gutiérrez, Luis J Manso, Harit Pandya, Pedro Núñez
Object detection and classification have countless applications in human-robot interacting systems. It is a necessary skill for autonomous robots that perform tasks in household scenarios. Despite the great advances in deep learning and computer vision, social robots performing non-trivial tasks usually spend most of their time finding and modeling objects. Working in real scenarios means dealing with constant environment changes and relatively low-quality sensor data due to the distance at which objects are often found...
February 11, 2017: Sensors
https://www.readbyqxmd.com/read/28208587/vehicle-detection-in-aerial-images-based-on-region-convolutional-neural-networks-and-hard-negative-example-mining
#8
Tianyu Tang, Shilin Zhou, Zhipeng Deng, Huanxin Zou, Lin Lei
Detecting vehicles in aerial imagery plays an important role in a wide range of applications. The current vehicle detection methods are mostly based on sliding-window search and handcrafted or shallow-learning-based features, having limited description capability and heavy computational costs. Recently, due to the powerful feature representations, region convolutional neural networks (CNN) based detection methods have achieved state-of-the-art performance in computer vision, especially Faster R-CNN. However, directly using it for vehicle detection in aerial images has many limitations: (1) region proposal network (RPN) in Faster R-CNN has poor performance for accurately locating small-sized vehicles, due to the relatively coarse feature maps; and (2) the classifier after RPN cannot distinguish vehicles and complex backgrounds well...
February 10, 2017: Sensors
https://www.readbyqxmd.com/read/28207397/stacked-learning-to-search-for-scene-labeling
#9
Feiyang Cheng, Xuming He, Hong Zhang
Search-based structured prediction methods have shown promising successes in both computer vision and natural language processing recently. However, most existing search-based approaches lead to a complex multi-stage learning process, which is ill-suited for scene labeling problems with a high-dimensional output space. In this paper, a stacked learning to search method is proposed to address scene labeling tasks. We design a simplified search process consisting of a sequence of ranking functions, which are learned based on a stacked learning strategy to prevent over-fitting...
February 13, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28204987/the-effects-of-topical-carbonic-anhydrase-inhibitor-in-treatment-of-nystagmus
#10
Ebru Demet Aygit, Osman Bulut Ocak, Aslı İnal, Korhan Fazıl, Serpil Akar, Birsen Gokyigit
OBJECTIVE: To evaluate the effects of topical carbonic anhydrase inhibitor (CAI), brinzolamide (Azopt), for treatment of nystagmus patients. MATERIALS AND METHODS: Patients who used Brinzolamide for treatment of nystagmus were retrospectively analyzed. 23 patients were included in this study. The patients' diagnosis were idiopathic infantile nystagmus 18 (78.2%) and oculocutaneous albinism in 5 (21.8%). Azopt eye drop was used in both eyes, 3 times a day. Detailed eye examination in all of the patients before treatment and repeated at the end of the first week after treatment...
February 15, 2017: International Ophthalmology
https://www.readbyqxmd.com/read/28202301/preoperative-assessment-of-the-ureter-with-dual-phase-contrast-enhanced-computed-tomography-for-lateral-lumbar-interbody-fusion-procedures
#11
Shunsuke Fujibayashi, Bungo Otsuki, Hiroaki Kimura, Shimei Tanida, Kazutaka Masamoto, Shuichi Matsuda
BACKGROUND: Performing the minimally invasive lateral lumbar interbody fusion (LIF), such as the extreme lateral interbody fusion (XLIF) and oblique lateral interbody fusion (OLIF), through a retroperitoneal approach has become increasingly popular. Although urological injury is a major complication of LIF, the anatomical location of the ureter and its risk of injury have not been assessed. The purpose of this study was to evaluate the efficacy of dual-phase contrast-enhanced computed tomography for assessing the location of the ureter and risk of its injury in consecutive LIF cases...
February 12, 2017: Journal of Orthopaedic Science: Official Journal of the Japanese Orthopaedic Association
https://www.readbyqxmd.com/read/28194800/grain-classifier-with-computer-vision-using-adaptive-neuro-fuzzy-inference-system
#12
Kadir Sabanci, Abdurrahim Toktas, Ahmet Kayabasi
BACKGROUND: A computer vision-based classifier using adaptive neuro-fuzzy inference system (ANFIS) is designed for classifying wheat grains into bread or durum. To train and test the classifier, images of 200 wheat grains (100 for bread and 100 for durum) are taken by a high resolution camera. Visual feature data of the grains related to dimension (#4), colour (#3) and texture (#5) as inputs of the classifier is mainly acquired for each grain using image processing techniques (IPTs). In addition to this main data, 9 features are reproduced from the main features to ensure a varied population...
February 13, 2017: Journal of the Science of Food and Agriculture
https://www.readbyqxmd.com/read/28193871/optimizing-virtual-reality-for-all-users-through-gaze-contingent-and-adaptive-focus-displays
#13
Nitish Padmanaban, Robert Konrad, Tal Stramer, Emily A Cooper, Gordon Wetzstein
From the desktop to the laptop to the mobile device, personal computing platforms evolve over time. Moving forward, wearable computing is widely expected to be integral to consumer electronics and beyond. The primary interface between a wearable computer and a user is often a near-eye display. However, current generation near-eye displays suffer from multiple limitations: they are unable to provide fully natural visual cues and comfortable viewing experiences for all users. At their core, many of the issues with near-eye displays are caused by limitations in conventional optics...
February 13, 2017: Proceedings of the National Academy of Sciences of the United States of America
https://www.readbyqxmd.com/read/28192624/mr-based-synthetic-ct-generation-using-a-deep-convolutional-neural-network-method
#14
Xiao Han
PURPOSE: Interests have been rapidly growing in the field of radiotherapy to replace CT with magnetic resonance imaging (MRI), due to superior soft tissue contrast offered by MRI and the desire to reduce unnecessary radiation dose. MR-only radiotherapy also simplifies clinical workflow and avoids uncertainties in aligning MR with CT. Methods, however, are needed to derive CT-equivalent representations, often known as synthetic CT (sCT), from patient MR images for the purpose of dose calculation and DRR-based patient positioning...
February 13, 2017: Medical Physics
https://www.readbyqxmd.com/read/28186883/detection-and-localization-of-robotic-tools-in-robot-assisted-surgery-videos-using-deep-neural-networks-for-region-proposal-and-detection
#15
Duygu Sarikaya, Jason Corso, Khurshid Guru
Video understanding of robot-assisted surgery (RAS) videos is an active research area. Modeling the gestures and skill level of surgeons presents an interesting problem. The insights drawn may be applied in effective skill acquisition, objective skill assessment, real-time feedback, and human-robot collaborative surgeries. We propose a solution to the tool detection and localization open problem in RAS video understanding, using a strictly computer vision approach and the recent advances of deep learning. We propose an architecture using multimodal convolutional neural networks for fast detection and localization of tools in RAS videos...
February 8, 2017: IEEE Transactions on Medical Imaging
https://www.readbyqxmd.com/read/28184316/perceptual-distortions-and-deceptions-what-computers-can-teach-us
#16
Matthew M Nour, Joseph M Nour
The nature of perception has fascinated philosophers for centuries, and has more recently been the focus of research in psychology and neuroscience. Many psychiatric disorders are characterised by perceptual abnormalities, ranging from sensory distortions to illusions and hallucinations. The distinction between normal and abnormal perception is, however, hard to articulate. In this article we argue that the distinction between normal perception and abnormal perception is best seen as a quantitative one, resting on the degree to which the observer's prior expectations influence perceptual inference...
February 2017: BJPsych Bulletin
https://www.readbyqxmd.com/read/28182555/comparative-validation-of-polyp-detection-methods-in-video-colonoscopy-results-from-the-miccai-2015-endoscopic-vision-challenge
#17
Jorge Bernal, Nima Tajbakhsh, F Javier Sanchez, Bogdan J Matuszewski, Hao Chen, Lequan Yu, Quentin Angermann, Olivier Romain, Bjorn Rustad, Ilangko Balasingham, Konstantin Pogorelov, Sungbin Choi, Quentin Debard, L Maier-Hein, Stefanie Speidel, Danail Stoyanov, Patrick Brandao, Henry Cordova, Cristina Sanchez-Montes, Suryakanth R Gurudu, Gloria Fernandez-Esparrach, Xavier Dray, Jianming Liang, Aymeric Histace
Colonoscopy is the gold standard for colon cancer screening though still some polyps are missed, thus preventing early disease detection and treatment. Several computational systems have been proposed to assist polyp detection during colonoscopy but so far without consistent evaluation. The lack of publicly available annotated databases has made it difficult to compare methods and to assess if they achieve performance levels acceptable for clinical use. The Automatic Polyp Detection subchallenge, conducted as part of the Endoscopic Vision Challenge (http://endovis...
February 2, 2017: IEEE Transactions on Medical Imaging
https://www.readbyqxmd.com/read/28168112/what-has-been-missed-for-predicting-human-attention-in-viewing-driving-clips
#18
Jiawei Xu, Shigang Yue, Federica Menchinelli, Kun Guo
Recent research progress on the topic of human visual attention allocation in scene perception and its simulation is based mainly on studies with static images. However, natural vision requires us to extract visual information that constantly changes due to egocentric movements or dynamics of the world. It is unclear to what extent spatio-temporal regularity, an inherent regularity in dynamic vision, affects human gaze distribution and saliency computation in visual attention models. In this free-viewing eye-tracking study we manipulated the spatio-temporal regularity of traffic videos by presenting them in normal video sequence, reversed video sequence, normal frame sequence, and randomised frame sequence...
2017: PeerJ
https://www.readbyqxmd.com/read/28167406/comparing-humans-and-deep-learning-performance-for-grading-amd-a-study-in-using-universal-deep-features-and-transfer-learning-for-automated-amd-analysis
#19
Philippe Burlina, Katia D Pacheco, Neil Joshi, David E Freund, Neil M Bressler
BACKGROUND: When left untreated, age-related macular degeneration (AMD) is the leading cause of vision loss in people over fifty in the US. Currently it is estimated that about eight million US individuals have the intermediate stage of AMD that is often asymptomatic with regard to visual deficit. These individuals are at high risk for progressing to the advanced stage where the often treatable choroidal neovascular form of AMD can occur. Careful monitoring to detect the onset and prompt treatment of the neovascular form as well as dietary supplementation can reduce the risk of vision loss from AMD, therefore, preferred practice patterns recommend identifying individuals with the intermediate stage in a timely manner...
January 27, 2017: Computers in Biology and Medicine
https://www.readbyqxmd.com/read/28165365/camber-angle-inspection-for-vehicle-wheel-alignments
#20
Jieh-Shian Young, Hong-Yi Hsu, Chih-Yuan Chuang
This paper introduces an alternative approach to the camber angle measurement for vehicle wheel alignment. Instead of current commercial approaches that apply computation vision techniques, this study aims at realizing a micro-control-unit (MCU)-based camber inspection system with a 3-axis accelerometer. We analyze the precision of the inspection system for the axis misalignments of the accelerometer. The results show that the axes of the accelerometer can be aligned to the axes of the camber inspection system imperfectly...
February 3, 2017: Sensors
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