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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17 views

Exctracting features for image captioning

If I want to do image captioning on a datasets, what are the steps I need to do that if I'm using object detection model? Should I freeze layers or not? The steps in my mind are Get the features from ...
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1answer
220 views

When training a CNN, what are the hyperparameters to tune first?

I am training a convolutional neural network for object detection. Apart from the learning rate, what are the other hyperparameters that I should tune? And in what order of importance? Besides, I read ...
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10 views

How to change a single object detection network to a multiple object detection network?

I have trained a CNN network to detect a circle and approximate its centre and radius in an image. What I want to do now is detect the centre and radius of all the circles if there are multiple ...
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6 views

Bounding box transformation using point cloud

I am working on a project in which I have an RGB Image and the corresponding 2d bounding boxes for the objects in the image. I also have a respective point cloud and therefore, I can extract the depth ...
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1answer
90 views

What do we 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 seems to deal with this idea in a highly mathematical ...
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2answers
41 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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1answer
19 views

Changing a CNN-LSTM image captioning architecture to use BiLSTMs

Currently I'm dealing with an assignment that made us implement the network mentioned in this paper. The network has an architecture similar to this: As you can see it uses a Unidirectional RNN (in ...
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11 views

Why the collection of background/negative image dataset is not taught in object detection tutorials and books?

While I was doing an object detection project, I have encountered the problem of getting FALSE POSITIVES and FALSE NEGATIVES. After days of research on StackOverflow, I figured out that I need to ...
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4answers
90 views

How much statistics is involved in AI?

This may be a stupid question but I couldn't really find an answer on the internet. I am a 3rd year math major who is interested in computer science, particularly algorithms and competitive ...
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20 views

How to remember previously detected objects in computer vision?

Let's say I have a drone that has to fly (and scan) over some area (blue on the images - in this case a PV power plant, but it could be anything) in an autonomous way like in the pic below: Let's ...
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8 views

How to measure(classify) the speed of oncoming traffic via Computer Vision and Neural Networks?

Suppose I have different videos of the same car sometimes moving slow, sometimes moving fast, say, at 50Kmph as slow and 60Kmph as fast. (Assume the background is a green screen and the car doesn't ...
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1answer
52 views

Is it possible to use self-supervised learning on different images for the pretext and downstream tasks?

I have just come across the idea of self-supervised learning. It seems that it is possible to get higher accuracies on downstream tasks when the network is trained on pretext tasks. Suppose that I ...
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18 views

What are the most relevant resources that define the face detection problem formally?

I am new to AI, and I am a bit lost about finding the relevant materials that define the face detection problem formally/mathematically. Can anyone help me formally define face detection, or at least ...
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1answer
70 views

What is a heatmap in the CornerNet paper?

I have been working on understanding how CornerNet works, but I couldn't figure out a few parts about the architecture. First, the authors mention that there are 3 distinct parts to be predicted as a ...
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1answer
48 views

How to use 'Canny/Watershed' algorithm's output as an input for Image Classification Model

I have a very silly problem in hand. I have implemented 2 methods which give me the mask to separate the objects from the background. What I get from one method is the object encapsulated in the red ...
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3answers
160 views

Neural Network that Predicts Game State Based on Actions

I am trying to find literature on a network architecture that takes the following as in input: Action (like 'Up', 'Down', etc) Image of current state and outputs: Image of next state I already ...
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1answer
156 views

What should load_mask() return if an image doesn't have any objects? (Mask RCNN)

I want to use Mask RCNN to do image segmentation. I need to override the load_mask function for the dataset class. I know this function should return mask tensors and class ids of objects in an image. ...
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6 views

Arcface implementation for image similarity produces opposite embeddings for positive negative image pairs

So I've built an arcface model with this arcface layer implementation: https://github.com/4uiiurz1/keras-arcface/blob/master/metrics.py I trained for a few epochs and now that I'm comparing the ...
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1answer
112 views

How do I segment each part of a DICOM image?

As I'm beginner in image processing, I am having difficulty in segmenting all the parts in DICOM image. Currently, I'm applying watershed algorithm, but it segments only that part that has tumour. ...
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1answer
60 views

How to normalize for perceptual loss when training neural net from scratch?

Let's say we are training a new neural network from scratch. I calculate the mean and standard deviation of my dataset (assume I am training a fully convolutional neural net and my dataset is images) ...
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1k views

Do deep learning algorithms represent ensemble-based methods?

According to the Wikipedia article on deep learning: Deep learning is a branch of machine learning based on a set of algorithms that attempt to model high-level abstractions in data by using a deep ...
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3answers
38 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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1answer
39 views

Is intersection of labels acceptable in computer vision?

I have a dataset, where objects are very close to each other. So, the question is: what is the best approach to label them? There are two possible options: mark objects so that they will not ...
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1answer
49 views

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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2answers
64 views

Unet Overfitting for binary segmentation of fake images

I am working on a project where I am trying to detect and localize forgeries in images. I am using the CASIA v2 dataset and using Unet model for the task. I have the binary masks of all the images in ...
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9 views

how to use Laplacian of mesh structure (LBO) for meshes that are registered in deep learning methods based on spectrum (ChebNet for isntance)?

In graph neural network frameworks, there is always a template with a shared structure among all graphs. I have meshes that are registered but obviously, Lalpalcian and their geometry are different. ...
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21 views

Is it possible to do object detection on an object classification dataset?

I'm new to computer vision, which I find fascinating. I wonder whether it is possible or if there has been any research into going from object recognition data to object detection. In other words, ...
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22 views

Which layer to route out of layers of same width and height in Yolo implementation?

In Yolo configuration files (like yolo3.cfg in dark-net), there are many layers with output of same height and width due to ...
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10 views

Can I get some advices on inferencing people from upwards using Yolov5?

I'm trying to inference people from upwards and count them using Yolov5. I know the controversy between yolov5 and yolov4, but for me, Yolov5 is more easier and reliable to use, also the setup. I have ...
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1answer
265 views

Which neural networks are suitable for visual place recognition?

I am doing a project on visual place recognition in changing environments. The CNN used here is mostly AlexNet, and a feature vector is constructed from layer 3. Does anyone know of similar work ...
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1answer
35 views

Training a model to identify certain differences between images?

Newbie to CV here so sorry of this is basic. Here's the deal, I have a program that I run many times. and each run I produce a screenshot. I need to compare screenshots from N-1 and N runs and make ...
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11 views

How to obtain part filter anchors in DPM Detector

The DPM detector (https://cs.brown.edu/people/pfelzens/papers/lsvm-pami.pdf) uses latent-svm to train the weights of the root and part filters. During training for positive samples, it alternates ...
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7 views

Should I L-2 Normalise outputs in Siamese Neural Neural Network for distance computation for Triplet Loss or not?

I am building a Siamese Neural Network for Images (CNN) which uses the FaceNet's Triplet Loss as its loss function. I found a good Implementation here where we build a model and the outputs from the ...
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30 views

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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2answers
84 views

How to recognize sequence of digits in an image

I am learning to program neural networks and others, and I would like to know how I can get the numbers that are in an image, for example, if I pass an image that has 123 written, get with my model ...
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2answers
44 views

Should I use U-net to label keys in a keyboard image?

This is a 600*800 image. Which algorithm/model should I use to get an image like the one below, in which each key is detected and labeled by a rectangle? I guess this is some kind of a segmentation ...
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444 views

Algorithms for scene rotation

My goal is to take an image and return another image that looks as if the scene was viewed from another angle. The difference in angle can be small — let's say as if the hand holding the camera moved ...
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1answer
60 views

Extracting Descriptors and feature points for 3d mesh

I'm programming my work with python, and I have a mesh and I want to extract 3d descriptors and feature points from it( trying to work on multi-scale strategy) , to visualize them later on the mesh, ...
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1answer
766 views

How feasible is it to perform pose estimation on a Raspberry Pi 4 using a Pi-Cam?

I want to estimate hand poses and recognize gestures using an open-source library like OpenPose on live video. Considering the fact that such libraries are very computationally intensive. How likely ...
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1answer
58 views

What are some good papers or resources for aspect extraction and opinion modelling from video or audio?

I am quite new to deep learning. I just finished the deep learning specialization by Professor Andrew NG and Deep Learning AI. Now, my professor (instructor) has advised me to look into some classic ...
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1answer
517 views

Alternative to sliding window neural network (was: Object detect (or) image classification at specific locations in the frame)

Recent advances in Deeplearning and dedicated hardware has made it possible to detect images with a much better accuracy than ever. Neural networks are the gold standard for computer vision ...
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1answer
39 views

Viola-Jones algorithm: Haar-like features, how are the features extracted?

If I have an image like this 1 2 3 4 5 6 7 8 a b c d e f g h ... And I apply a Haar-like feature with a template ...
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1answer
273 views

Is Mask R-CNN suited to solve a multi-class classification problem where the classes are related?

I want to create a model to solve a multi-class classification problem. Here are more details about my problem. Every picture contains only one object The background is very simple All objects ...
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3answers
140 views

If I trained a model to perform semantic segmentation on images with only one object, would it also work on images with multiple objects?

I'm working on semantic segmentation tasks in the medical space using the U-Net. Let's say that I train a U-Net model on medical images with the goal of segmenting out, say, ligaments, from a medical ...
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1answer
124 views

How to choose a suitable threshold value for shi-tomasi corner detection algorithm?

While implementing shi-tomasi corner detection algorithm i got stuck at deciding a suitable threshold for corner detection. In shi-tomasi algorithm all those points that qualify ...
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1answer
79 views

What is the current state of the art in animal facial recognition?

As far as I can tell, most work on facial recognition has been done in relation to human faces. Has any significant work been done for dogs, and are there any special challenges that would make it ...
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1answer
1k views

Are information processing rules from Gestalt psychology still used in computer vision today?

Decades ago there were and are books in machine vision, which by implementing various information processing rules from gestalt psychology, got impressive results with little code or special hardware ...
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1answer
140 views

Can a fully convolutional network always return an image of the same size as the original?

I'm trying to perform a segmentation task on images of multiple sizes using fully convolutional neural networks. Currently, I'm using EfficientNet as a feature extractor, and adding a deconvolution/...
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1answer
54 views

Video summarization similar to Summe's TextRank

We have the popular TextRank API which given a text, ranks keywords and can apply summarization given a predefined text length. I am wondering if there is a similar tool for video summarization. ...
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35 views

Is it likely that a sentient AI experience synesthesia?

The reason I ask this question is because we humans tend to compartmentalize our sensory inputs, except in some individuals that experience synesthesia. If an Artificial Intelligence Entity (AIE) can ...

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