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arXiv 2025年

作者： Tai, Chi-En Amy Tannier, Xavier University of Waterloo Vision and Image Processing Lab VIP 200 University Avenue West WaterlooN2L3G1 Canada Sorbonne Université INSERM Université Sorbonne Paris-Nord Laboratoire d’Informatique Médicale et d’Ingénierie des Connaissances en eSanté LIMICS 15 rue de l’école de médecine Paris75006 France

Clinical trials are a critical process in the medical field for introducing new treatments and innovations. However, cohort selection for clinical trials is a time-consuming process that often requires manual review of patient text records for specific keyword. Though there have been studies on standardizing the information across the various platforms, Natural Language processing (NLP) tools remain crucial for spotting eligibility criteria in textual reports. Recently, pre-trained large language models (LLMs) have gained popularity for various NLP tasks due to their ability to acquire a nuanced understanding of text. In this paper, we study the performance of large language models on clinical trial cohort selection and leverage the n2c2 challenges to benchmark their performance. Our results are promising with regard to the incorporation of LLMs for simple cohort selection tasks, but also highlight the difficulties encountered by these models as soon as fine-grained knowledge and reasoning are required. Copyright © 2025, The Authors. All rights reserved.

关键词： Natural language processing systems

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Seeing Beyond the Crop: Using Language Priors for Out-of-Bounding Box Keypoint Prediction 38

Seeing Beyond the Crop: Using Language Priors for Out-of-Bou...

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38th Conference on Neural Information processing Systems, NeurIPS 2024

作者： Balaji, Bavesh Bright, Jerrin Chen, Yuhao Rambhatla, Sirisha Zelek, John S. Clausi, David Anthony Critical ML Lab Vision and Image Processing Lab University of Waterloo Canada

Accurate estimation of human pose and the pose of interacting objects, like a hockey stick, is crucial for action recognition and performance analysis, particularly in sports. Existing methods capture the object along with the human in the bounding boxes, assuming all keypoints are visible within the bounding box. This necessitates larger bounding boxes to capture the object, introducing unnecessary visual features and hindering performance in real-world cluttered environments. We propose a simple image and text-based multimodal solution TokenCLIPose that addresses this limitation. Our approach focuses solely on human keypoints within the bounding box, treating objects as unseen. TokenCLIPose leverages the rich semantic representations endowed by language for inducing keypoint-specific context, even for occluded keypoints. We evaluate the performance of TokenCLIPose on a real-world ice hockey dataset, and demonstrate its generalizability through zero-shot transfer to a smaller Lacrosse dataset. Additionally, we showcase its flexibility on CrowdPose, a popular occlusion benchmark with keypoints within the bounding box. Our method significantly improves over state-of-the-art approaches on ice hockey, Lacrosse, and CrowdPose datasets, with gains of 4.36%, 2.35%, and 3.8%, respectively. © 2024 Neural information processing systems foundation. All rights reserved.

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Precise high speed multi-target multi-sensor local positioning system

Precise high speed multi-target multi-sensor local positioni...

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Canadian Conference on Computer and Robot vision

作者： Eichel, Justin A. Clausi, David A. Fieguth, Paul Vision and Image Processing Lab. University of Waterloo Waterloo Canada

ISBN: (纸本)9780769543628

When used for tracking, the combination of infrared (IR) and an internal measurement unit (IMU) allows researchers and industry to locate objects to within 1 cm at over 200 Hz with a latency less than 2 ms. This novel tracking system uses multiple cameras to triangulate an IR LED placed on the object and utilizes IMU data to measure the object's orientation and allow the system to be robust against visual occlusions. The cost-effective IR system is robust against illumination allowing the object to be tracked at over 50 feet from the camera positions. This distance is expected to increase with additional development. This paper describes the preliminary algorithms that utilize the information from both the IR and IMU systems in order to precisely track an object. The algorithms are tested against simulated data generated from profiling the hardware and real data collected from a system prototype. © 2011 IEEE.

关键词： Cost effectiveness

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Dictionary replacement for single image restoration of 3D scenes 27

Dictionary replacement for single image restoration of 3D sc...

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27th British Machine vision Conference, BMVC 2016

作者： Nimisha, T.M. Arun, M. Rajagopalan, A.N. Image Processing and Computer Vision Lab Indian Institute of Technology Madras Chennai India

In this paper, we address the problem of jointly estimating the latent image and the depth/blur map from a single space-variantly blurred image using dictionary learning. The approach taken is based on the central idea of dictionary replacement viz. the sparse representation of a blurred image over a blurred dictionary is equivalent to that over a clean dictionary. While most of the dictionary-based deblurring methods consider planar scenes with space-invariant blur, we handle 3D scenes with space-variant blur caused by either camera motion or optical defocus. For a given blurred image, the dictionary blurred with the corresponding blur kernel provides the best representation with the least error. We formulate our problem of blur map and latent image estimation as a multi-label MRF and solve it using graph-cut. Experimental results on defocus as well as motion blur depict the effectiveness of our scheme. © 2016. The copyright of this document resides with its authors.

关键词： image reconstruction

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Random number generators: Metrics and tests for uniformity and randomness

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Journal of Combinatorial Mathematics and Combinatorial Computing 2010年 74卷 161-180页

作者： Yfantis, E.A. Pedersen, J.B. Image Processing Computer Vision and Machine Intelligence Lab College of Engineering 4505 Maryland Parkway Las Vegas NV 89154-4019 United States

Random number generators are a small part of any computer simulation project. Yet they are the heart and the engine that drives the project. Often times software houses fail to understand the complexity involved in building a random number generator that will satisfy the project requirements and will be able to produce realistic results. Building a random number generator with a desirable periodicity, that is uniform, that produces all the random permutations with equal probability, and at random, is not an easy task. In this paper we provide tests and metrics for testing random number generators for uniformity and randomness. These tests are in addition to the already existing tests for uniformity and randomness, which we modify by running each test a large number of times on sub-sequences of random numbers, each of length n. The test result obtained each time is used to determine the probability distribution function. This eliminates the random number generator misclassification error. We also provide new tests for uniformity and randomness, the new tests for uniformity test the skewness of each one of the subgroups as well as the kurtosis. The tests for randomness, which include the Fourier spectrum, the phase spectrum, the discrete cosine transform spectrum, and the orthogonal wavelet domain, test for patterns not detected in the row data space. Finally we provide visual and acoustic tests.

关键词： Discrete cosine transforms

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Contourlet transform based moving object segmentation

Contourlet transform based moving object segmentation

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2013 IEEE Conference on Information and Communication Technologies, ICT 2013

作者： Khare, Manish Nigam, Swati Srivastava, Rajneesh Kumar Khare, Ashish Image Processing and Computer Vision Lab Department of Electronics and Communication University of Allahabad Allahabad India

ISBN: (纸本)9781467357586

Moving object segmentation is an important step toward development of any computer vision systems. In the present work, we have proposed a new method for segmentation of moving objects, which is based on single change detection method applied on Contourlet coefficients of two consecutive frames. We have chosen contourlet transform as it has high directionality and represents salient features of image such as edges, curves and contours in better way as compared with wavelet transform. The proposed method is simple and does not require any other parameter except contourlet coefficients. Results after applying the proposed method for segmentation of moving objects are compared with other state-of-the-art methods in terms of visual as well as quantitative performance measures viz. Average difference, Normalized absolute error and Pixel classification based measure. The proposed method is found to be better than other methods. © 2013 IEEE.

关键词： Contourlet transform

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Efficient Bayesian inference using fully connected conditional random fields with stochastic cliques

Efficient Bayesian inference using fully connected condition...

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作者： Shafiee, M.J. Wong, A. Siva, P. Fieguth, P. Vision and Image Processing Lab System Design Engineering Dept. University of Waterloo Canada

ISBN: (纸本)9781479957514

Conditional random fields (CRFs) are one of the most powerful frameworks in image modeling. However practical CRFs typically have edges only between nearby nodes;using more interactions and expressive relations among nodes make these methods impractical for large-scale applications, due to the high computational complexity. Recent work has shown that fully connected CRFs can be tractable by defining specific potential functions. In this paper, we present a novel framework to tackle the computational complexity of a fully connected graph without requiring specific potential functions. Instead, inspired by random graph theory and sampling methods, we propose a new clique structure called stochastic cliques. The stochastically fully connected CRF (SFCRF) is a marriage between random graphs and random fields, benefiting from the advantages of fully connected graphs while maintaining computational tractability. The effectiveness of SFCRF was examined by binary image labeling of highly noisy images. The results show that the proposed framework outperforms an adjacency CRF and a CRF with a large neighborhood size. © 2014 IEEE.

关键词： Computational complexity

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Efficient geometric matching with higher-order features

Efficient geometric matching with higher-order features

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作者： Paramanand, C. Rajagopalan, A.N. Image Processing and Computer Vision Lab. Department of Electrical Engineering IIT Madras India

ISBN: (纸本)9781424421756

We propose a new technique in which line segments and elliptical arcs are used as features for recognizing image patterns. By using this approach, the process of locating a model in a given image is efficient since the number of features to be compared is few. We propose distance measures to evaluate the similarity between the features of the model and that of the image. The model transformation parameters are found by searching the transformation space using cell decomposition. © 2008 IEEE.

关键词： Pattern recognition

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Hierarchical Attention Approach in Multimodal Emotion Recognition for Human Robot Interaction 36

Hierarchical Attention Approach in Multimodal Emotion Recogn...

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36th International Technical Conference on Circuits/Systems, Computers and Communications, ITC-CSCC 2021

作者： Abdullah, Muhammad Ahmad, Mobeen Han, Dongil Vision and Image Processing Lab Sejong University Department of Computer Engineering Seoul Korea Republic of

ISBN: (纸本)9781665435536

The ability to perceive human emotions is one of the key elements that may promise a natural, genuine and more reliable human robot interaction. Though emotional perception in human robot interaction has been challenged by many difficulties, the lack of contextual understanding is can be attributed as the biggest hurdle in this regard. Most of the literature refers to the datasets developed in controlled environment to validate the performance of their systems which happens to be really good. Still those systems are very far from achieving that kind of performance in real-life scenarios. In this paper a multimodal emotion recognition strategy is presented, that uses voice features in addition to the facial expressions to determine the emotional state of the user. A hierarchical attention layer is used to for feature fusion purpose. The final system is end-to-end trainable, multimodal approach makes it more resilient to the changes in environment. The achieved 76.3% accuracy for eNterface05 video dataset, which is higher than the any single modality approach in the comparison. © 2021 IEEE.

关键词： Emotion Recognition

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CHASE: Robust Visual Tracking via Cell-Level Differentiable Neural Architecture Search 32

CHASE: Robust Visual Tracking via Cell-Level Differentiable ...

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32nd British Machine vision Conference, BMVC 2021

作者： Marvasti-Zadeh, Seyed Mojtaba Khaghani, Javad Cheng, Li Ghanei-Yakhdan, Hossein Kasaei, Shohreh Vision and Learning Lab University of Alberta Edmonton Canada Digital Image & Video Processing Lab Yazd University Yazd Iran Image Processing Lab Sharif University of Technology Tehran Iran

A strong visual object tracker nowadays relies on its well-crafted modules, which typically consist of manually-designed network architectures to deliver high-quality tracking results. Not surprisingly, the manual design process becomes a particularly challenging barrier, as it demands sufficient prior experience, enormous effort, intuition, and perhaps some good luck. Meanwhile, neural architecture search has gaining grounds in practical applications as a promising method in tackling the issue of automated search of feasible network structures. In this work, we propose a novel cell-level differentiable architecture search mechanism with early stopping to automate the network design of the tracking module, aiming to adapt backbone features to the objective of Siamese tracking networks during offline training. Besides, the proposed early stopping strategy avoids over-fitting and performance collapse problems leading to generalization improvement. The proposed approach is simple, efficient, and with no need to stack a series of modules to construct a network. Our approach is easy to be incorporated into existing trackers, which is empirically validated using different differentiable architecture search-based methods and tracking objectives. Extensive experimental evaluations demonstrate the superior performance of our approach over five commonly-used benchmarks. © 2021. The copyright of this document resides with its authors.

关键词： Network architecture

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