Questions tagged [computer-vision]

For questions related to computer vision, which is an interdisciplinary scientific field (which can e.g. use image processing techniques) that deals with how computers can be made to gain high-level understanding from digital images or videos. For example, image recognition (that is, the identification of the type of objects in an image) is a computer vision problem.

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15 views

Deep Learning based image restoration using multiple frames

Suppose we have a sequence of still images each of which has been contaminated by some particles(ex, dust/sand/smoke) making the images very poor in certain areas. What architecture would be best to ...
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Are there any known models/techniques to determine whether a person in a store is a customer or a store representative?

Are there any known models/techniques to determine whether a person in a store is a customer or a store representative? For example, customer representatives can wear uniforms and then one possible ...
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Are Markov Random Fields and Conditional Random Fields still used in computer vision?

Back before deep learning, there were a lot of different attempts at computer vision. Some involved Conditional Random Fields and Markov Random Fields, which were both computationally difficult and ...
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Computer vision - Can you put more weight on a specific part of the object?

Let's say I'm looking for any item that has a certain shape (outline) in a photo. but I can further classify it only according to particular features, that most of them are expected to be shown only ...
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What is the need for so many filters in a CNN?

Consider the following coding line related to CNNS Conv2D(64, (3,3), strides=(2, 2), padding='same') It is a convolution layer with filter size $3 \times 3$ and ...
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How can I train a CNN to detect when a person is smoking outside of shop given images from a video camera?

My friend is working at a pizza shop. He takes cigarette breaks in an area that is covered by the public webcam of our town. I now want to train a convolutional neural network to be able to detect ...
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Is training a CNN object detector on an image containing multiple targets that are not all annotated will teach it to miss targets?

I want to train a convolutional neural network for object detection (say YOLO) to detect faces. Consider this image: In this training image, I have many people, but only 2 of them are annotated. Is ...
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Why aren't the BERT layers frozen during fine-tuning tasks?

During transfer learning in computer vision, I've seen that the layers of the base model are frozen if the images aren't too different from the model on which the base model is trained on. However, on ...
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What is a wavefront algorithm?

I am designing and researching algorithms which I call of a wavefront nature. It is image analsyis agorithms when every pixel may change many times during the processing. I have heard this name before,...
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Formal definition of the Object Detection problem

For many problems in computer science, there is a formal, mathematical problem defition. Something like: Given ..., the problem is to ... How can the Object Detection problem (i.e. detecting objects ...
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How do you make a regression model from a binary labeled dataset?

Suppose I have a dataset with hand images. Hand completely opened is labeled as 0 and hand completely closed (fist) are labeled as 1. I also have a bunch of unlabeled images of hands which, if ...
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Train 3D object detection model for custom object

I am trying to train a model that can detect a 3D object and give me a 3D bounding box around it. For this, I have a RGBD camera and a 2D LiDAR. Most of the research is done for cars/cyclists/...
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How to use SPP-net and what are its drawbacks?

I read about the spatial pyramid pooling concept, it's really cool! Now, my doubt is how to find the number of layers to use, and in each layer what should be the grid sizes when using spp. But, I ...
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Would it be possible to use AI to measure pupil dilation diameters and fluctuation, on video films on a regular webcam?

I've been researching the topic of Cognitive Load Measurement through pupil dilation measurement. All solutions to pupil dilation measurement require some kind of special hardware setup. I was ...
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Can we identify only the objects in specific parts of an image with computer vision?

I am studying computer vision for the past 3 months. I have come across the object identification problem, where given an image, CV would identify various parts in the image. If I give an image, and a ...
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How to normalise image input to backpropogation algorithm?

I am implementing a simple backpropagation neural network for classifying images. One set of images are cars another set of images are buildings (houses). So far I have used Sobel Edge detector after ...
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1answer
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Is there any network/paper used to analyse music scores?

As I am curious on music theory I would like to know that If is there any such network that analyse like labeling chords, or doing a roman numeral analysis. Like an example below: Source It does not ...
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Why don't we use auto-encoders instead of GANs?

I have watched Stanford's lectures about artificial intelligence, I currently have one question: why don't we use autoencoders instead of GANs? Basically, what GAN does is it receives a random vector ...
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How can I calibrate 3 cameras and track the object using only synchronized cameras feeds from all the cameras?

I have camera feed (in the form of RGB images) from 3 cameras with partially overlapping Field-of-view i.e. for the time stamp 0 to 100, I have total 300 frames or say synchronized 100 RGB frames for ...
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How do non-local neural networks relate to attention and self-attention?

I've been reading non-local neural networks as explained in the original paper. My understanding is that they solve the restrained reception of local filters. I see how they are different from ...
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How is the data labelled in order to train a region proposal network?

I don't get how the training of the RPN works. From the forward propagation, I have $W \times H \times k$ outputs from the RPN. How is the training data labeled such that I can use the loss function ...
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Keeping track of multiple faces throughout a video

I have a video where multiple persons are seated. I need to keep track of the emotions they show throughout the video. My final result should be a csv file with all the emotions depicted by each ...
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How can traditional edge detection algorithms be implemented on a GPU?

How can edge detection algorithms, which are not based on deep learning, such as the canny edge detector, be implemented on a GPU? For example, how are non-edge pixels removed from an image once it ...
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Why isn't medical imaging improving faster with AI?

Researcher here. I just read this piece about medical imaging ai with object recognition and it left me wondering why there are still 100,000+ deaths a year in the US due to misdiagnosis - anyone out ...
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How can I calibrate 3 cameras without knowing global pose of the object & camera locations? How can I find the pose of each camera wrt the first one?

I have camera feed (in the form of RGB images) from 3 cameras with overlapping FOV e.g. for the time stamp 0 to 100, I have synchronized RGB frames for each camera. The object (Robot) is moving from ...
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23 views

How to train the images of various sizes?

I am practicing with an image dataset which is having different dimensions. If I simply crop and pad them to 1024X1024(the original images having smallest width is around 300 and largest is around ...
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How to decompose a non-positive definite matrix in the same manner as Cholseky decomposition?

I want to make a covariance matrix that incorporates my belief of how correlated the various dimensions are. The reason why I want to incorporate my belief is that in my modelling, the dimensions are ...
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Object detection using CNN model architectures

I've used LabelImg to create labels for my images using YOLO. After that, I would like to input the images and labels into a CNN model, like a VGG or ResNet. I've searched a lot and have not found ...
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How can I decrease the time to compute the mask in the Mask-RCNN for human body detection?

I am using Mask-RCNN to detect human bodies in photos, to get a rough approximation of the ratio of their heights to the length of their chests. I want to decrease the time for making the mask of the ...
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How to calculate the attention loss in the paper “Tell Me Where to Look: Guided Attention Inference Network”?

I have been reading the research paper Tell Me Where to Look: Guided Attention Inference Network. In this paper, they calculate the attention loss, but I didn't understand how to calculate it. Do we ...
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Why it is reshaped the last layers of VGG_UNet segmentation model?

I want to do a multiclass segmentation task using deep learning (in python). Here, is a summary of vgg_unet model that is mainly collected from GitHub. So, in my dataset 8 labels are available. So, at ...
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How to take the optimal batch_size for training a model?

I have an image dataset, which is composed of 113695 images for training and 28424 images for validation. Now, when I use ImageDataGenerator and ...
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Detect and overlay a black TV on a video

I have a short video where a TV is shown. I need to detect the TV there (let's assume it's all pure black or it's covered with a green screen), and overlay a video on top of it on the same area. I ...
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1answer
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What do you mean by 'Principal Angle between subspaces'

I came across the term 'Principal angle between Subspaces' as a tool for comparing objects in images. All material that I found on the internet seem to deal with this idea in a highly mathematical way ...
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How should I label images to get high accuracy with YOLO?

I am new to Object Detection with Yolo and I have questions regarding the labeling (for custom objects): Is there any guideline or tips on how to label images to have high accuracy at the end? ...
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31 views

Technology for predicting body measurements of a person, with a full body photo of them

I am working on making an app that would require the ratio of the height and the largest width of a person, in order to group the individual into a certain body fat percentage category. In short, I ...
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61 views

Is there any real-time computer vision system that can learn to detect new objects of new classes?

Suppose you have a ground plane and can use a stereo vision system to detect things that are possibly separate objects. Suppose also your robot or agent can attempt to pick up and move these objects ...
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What is the current way robots can assess and traverse difficult obstacles in 3d space?

What is the current way robots can assess and traverse difficult obstacles in 3d space? I could see manual feature extraction using stereo vision (for example, the height of the obstacle, "...
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How does YOLO handle non-class objects?

I have been reading more about computer vision and I'm bothered by YOLO and similar deep learning architectures. The thing I am confused on is how non-class image sections are dealt with, in ...
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Is there a problem for “Sound Source Identification in Video Footage”?

I've been considering starting a project for some time on sound source identification. To be more specific, my goal is to be able to identify the "sources" for sound in videos. Moving parts ...
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Is there a way to estimate odometry using a single camera without a depth map?

Is there a way to estimate odometry using a single camera without a depth map? It somewhat seems like a circular problem since to estimate movement you need to know the change in object size, but you ...
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How to develop a model to detect a point crossed a line?

How to develop a system which detects if a object crosses a line. I am developing a system, basically which tells a object crossed a line. Do I need to get the camera calibration matrix ? Do I need to ...
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Can I train an object detection model with images with a white background?

To be more specific I have a dataset of 2400 images with unbalanced classes, 1 object per image and sometimes some objects are repeated along the dataset but in a different position and rotation of ...
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What is the state-of-the-art algorithm for neural style transfer?

I've read the paper A Neural Algorithm of Artistic Style by Gatys et. al. and I find the application of neural style transfer very fun. I also read that Exploring the structure of a real-time, ...
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Does the selective search algorithm in object detection learn?

I am trying to get a better grasp of how object detection works. I (almost) completely understand the concept behind RPNs. However I am little bit confused with the selective search algorithm part. ...
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How to make sense of label propagation formula in graph neural networks?

In the label propagation algorithm in section 3.2.3, we know the label of some nodes and we want to predict the label for the rest of the nodes whose labels we don't know. The update formula for this ...
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Since both RoI Align and PrRoI Pooling use bilinear interpolation, why is RoI Align discrete while PrRoI Pooling continuous?

I have two questions. Since both use bilinear interpolation, why is RoI Align discrete while PrRoI Pooling continuous? Could anyone explain the intuition behind the derivative of PrPool()?
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Combining clustering and deep learning for computer vision

Is there any recent work on combining clustering approaches (k-means, or gaussian mixture or PGM) with deep learning for computer vision? In particular I'm interested in if anyone has used the first ...
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Why can we perform graph convolution using the standard 2d convolution with $1 \times \Gamma$ kernels?

Recently I was reading this paper Skeleton Based Action RecognitionUsing Spatio Temporal Graph Convolution. In this paper, the authors claim (below equation (\ref{9})) that we can perform graph ...
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What is meant by “arranging the final features of CNN in a grid” and how to do it?

In the paper What You Get Is What You See: A Visual Markup Decompiler, the authors have proposed a method to extract the features from the CNN and then arrange those extracted features in a grid to ...

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