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

Detect object in video and augment another video on top of it

I'm trying to detect an object in a video (with slight camera movement), and then augment another video on top of it. What is the simplest approach to do that? For instance, let's assume I have this ...
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How is visual attention mechanism different from a two branch convolutional neural network?

I am doing some research on the visual attention mechanism in remote sensing domain (where the features learnt from one layer are highlighted using the attention mask derived from another layer). From ...
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Merge two different CNN models into one

I have 2 different models with each model doing a separate function and have been trained with different weights. Is there any way I can merge these two models to get a single model. If it can be ...
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1answer
26 views

How does the math behind heat map filters work?

I am working on an app that generates heat/ thermal map given a picture. i have been able to get what i expected using python opencv builtin function ...
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1answer
33 views

How do you find the homography matrix given 4 points in both images?

I want to understand the process of finding a homography matrix given 4 points in both images. I am able to do that in python OpenCV, but I wonder how it works behind the scenes. Suppose I have ...
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6 views

How to feed decimal_y_values for training where last layer of model has 10 neurons with softmax activation and loss is Earth Mover Loss [migrated]

What should be the format/data types of y-labels for training if the actual y-labels cab be any decimal number between 0-9 (4.1,8.5 etc) and the last output layer is defined as: ...
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7 views

What is the advantages of using FPGA for deep learning- computer vision task? [migrated]

I noticed some developers prefer to use FPGA like XILINX for their deep learning applications, why they prefer to use FPGA instead of GPU?! Is there any reason for that? I suppose GPUs are very ...
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17 views

An Encoder-Decoder based CNN to predict a tensor of points

So I have with me a data of rendered 2D images of a 3D object and along with that, I have the image projection coordinates (X, Y) of all the voxels that are in the ...
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1answer
17 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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20 views

Why is this variable in equation 2 of the SQAIR paper a random vector of $n$ ones followed by a zero?

I've been reading the SQAIR paper lately, and the mathematics involved seems a bit complicated. Some background, about the paper: SQAIR stands for Sequential Attend, Infer, Repeat - the paper does ...
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1answer
19 views

Why do we set offset (0.5) in single shot detector?

In the paper SSD: Single Shot MultiBox Detector, under section 2.2 - (4), why do we add an offset of 0.5 to x, y in generating the anchor boxes across feature maps?
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How come a detection works after global average pooling 2D?

I use an off-the-shelf convolutional neural network, where at the end of the convolutional part, the depth of the last convolutional layer is expanded and then its 2D average is computed (such that ...
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1answer
44 views

What does the Fourier transformed image mean?

I have been trying to figure out what the Fourier transformed image represents. I am aware of Fourier transformation in general, but I can't explain myself the image it forms after transformation. ...
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1answer
34 views

Why are denser layers needed in computer vision neural nets?

Many neural net architectures for computer vision tasks use several convolutional layers and then several fully-connected (or dense) layers. While the reasons for using convolutional layers are clear ...
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15 views

What are the best human re-identification methods available?

I have a use case where I need to detect, track and re-identify humans in CCTV footage. I have usedSSD and Median Flow to detect ...
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2answers
54 views

Could machine learning be used to measure the distance between two objects from a picture or live camera?

Could machine learning be used to measure the distance between two objects from a picture or live camera? An example of this is the measurement between the centre of each eye pupil. This area is ...
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28 views

Creating Dataset for Image Classification

I want to develop a CNN model to identify 24 hand signs in American Sign Language. I created a custom dataset that contains 3000 images for each hand sign i.e. 72000 images in the entire dataset. For ...
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125 views

Understanding the results of “Visualizing and Understanding Convolutional Networks”

I am trying to understand the results of the paper Visualizing and Understanding Convolutional Networks, in particular the following image: What are these 3x3 blocks and their 9 cells representing? ...
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1answer
29 views

What is “natural image domain”?

I see some papers use the term "natural image domain". I googled that but didn't find any explanation of it. I guess I understand the normal meaning of "natural image", such as the image people take ...
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1answer
82 views

What does “off-the-shelf” mean?

I encountered the phrase/concept off-the-shelf CNN in this paper in which authors used off-the-shelf CNN representation, OverFeat, with simple classifiers to ...
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29 views

What are some real-world products or applications that can be developed using GANs?

GANs have shown good progress across a wide variety of domains ranging from image translation, image generation, text to image synthesis, audio/video generation, image super-resolution and many more. ...
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1answer
31 views

What is a landmark in computer vision?

I guess I understand the concept of face detection, a technique specifies the location of multiple objects in the image, and draws bounding boxes on the target. The question is related to the concept ...
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1answer
26 views

Before GAN, what are the commonly used techniques for image-to-image translation?

As per a post, image-to-image translation is a type of CV problem. I guess I understand the concept of image-to-image translation. I am aware that GANs(generative adversarial networks) are good at ...
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1answer
24 views

Running 10 epochs on the Food-101 dataset

I’m currently working on the Food-101 dataset. I want to train a model that is greater than 85% accuracy for top-1 for the test set, using a ResNet50 or smaller network with a reasonable set of ...
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1answer
21 views

How to estimate the accuracy upper limit of any CNN model over a computer vision classification task

We are given a computer vision classification task, that is, a task that asks us to predict the category of an image over $n$ predefined classes (the so-called closed set classification problem). ...
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14 views

How to output a filter of equal size to the original image in Fully Convolutional Neural networks

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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28 views

Why are conics important in computer vision?

The book Multiple View Geometry in Computer Vision by Richard Hartley and Andrew Zisserman talks about lines, points and conics. A conic is a curve described by a second-degree equation in the plane, ...
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26 views

Human Aggression Detection Community, Competition and dataset

I'm looking for a community or competition website related to human aggression detection using Deep Learning in a video. Also, I'm looking for a dataset of human aggression activities. Any ...
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1answer
85 views

How can I detect the frame from video streaming that contains a graffiti on city wall?

I am working on a graffiti detection project. I need to analyze data stream from a camera mounted sideways on a vehicle to identify graffiti on city walls and notify authorities with the single best ...
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1answer
42 views

What is the type of problem requiring to rate images on a scale?

I'm new to the topic, but I've used some off the shelf knowledge about computer vision for classifying images. For example, you can easily generate labels that can determine whether or not e.g. a ...
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24 views

Is there an efficient way of determining the layers with the best performance as feature extractors in GoogleNet?

I am using a caffe model of pre-trained GoogleNet trained on ImageNet from here for image retrieval task (place recognition, more specifically). I would like to know the layer with best performance ...
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2answers
70 views

Validation loss is lower than Training loss

I am training a classifier to identify 24 hand signs of American Sign Language. I created a custom dataset by recording videos in different backgrounds for each of the signs and later converted the ...
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18 views

Train an AI to infer accurate mathematical calculations by simply “looking” at images of shapes/objects

I’d like to build a model that has an understanding of geometry, where it can be applied to question and answering system. Specifically, it would be nice if it could determine the volume of an object ...
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21 views

Suitable algorithms for classifying terrain condition (asphalt, dirt etc) for motor vehicles

I am required to obtain data through a sensor located on the vehicle reading speed, vibration, roll and tilt, within a sample time, to classify the current road condition using machine learning for a ...
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42 views

Intuition behind single-shot object detection

Is there a good way to understand how single-shot object detection works? The most basic way to do detection is use a sliding-window detector and look at the output of the NN to detect if a class is ...
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2answers
34 views

What are the reasons behind slow YOLO training?

I'm testing out YOLOv3 using the 'darknet' binary, and custom config. It trains rather slow. My testing out is only with 1 image, 1 class, and using YOLOv3-tiny instead of YOLOv3 full, but the ...
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1answer
17 views

YOLOv3 Model Structure: Why is filters = (classes + coords + 1) * num?

Here's a tutorial about doing custom training of YOLO (Darknet): https://medium.com/@manivannan_data/how-to-train-yolov3-to-detect-custom-objects-ccbcafeb13d2 The tutorial guides how to set values in ...
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44 views

Does a fully convolutional network share the same translation invariance properties we get from networks that use max-pooling?

Does a fully convolutional network share the same translation invariance properties we get from networks that use max-pooling? If not, why do they perform as well as networks which use max-pooling?
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30 views

Weird border artifacts when training a CNN

I've been trying to use this DeepLabv3+ implementation with my dataset (~1000 annotated images of the same box, out of the same video sequence): https://github.com/srihari-humbarwadi/...
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35 views

What are the pros and cons of Keras, PyTorch and Caffe for computer vision?

I have tried to get the basic grasp of the following deep learning frameworks with python: Keras Pytorch Caffe However, I have lately noticed that people in the computer vision community care less ...
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10 views

What will be the sequence of steps in a human activity recognition model using LSTM?

In the context of these steps detection, tracking, action classification and activity recognition. Which step will be first and further sequence?
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1answer
21 views

Does bag-of-words method improve the classification accuracy?

I'm a beginner in computer vision. I want to know which structure among the following two can get better accuracy of image classification. Structure 1: SIFT feature + SVM Structure 2: bag-of-word ...
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0answers
20 views

What are the current tools and techniques for image segmentation in order of pragmatism?

To explain what I mean I'll depict the two extremes and something in the middle. 1) Most pragmatic: If you need to just segment a few images for a design project, forget AI. Go into Adobe Photoshop ...
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1answer
24 views

Interpolating image to increase resolution before feeding it to a neural network

Interpolation is a common way to make an image fit the right input shape for a neural network. But is there any point in using interpolation to make it easier for the network to learn? I assume ...
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51 views

How to encode 16bits PNG using cv2.imencode() in python? [closed]

I want to use cv2.imencode() to encode a 16 bits PNG image.The code in here: The 'depth' and 'data_encode' are as follows: We can find, the type of 'depth' is uint16, but the type of 'data_encode' ...
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10 views

How can a new metric applied for humans causing danger on railtracks?

I am writing myself and was thinking about, what kind of metric can be applied to measure the "dangerousness" of a human being on a railtrack? For example detecting if a human is running on the rails? ...
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1answer
177 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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25 views

What's the best solution to find distance of an object to camera?

I have an object with known size and I want to know that's the distance from the camera and camera angle. Is there any way to do this? I have a single source (camera).
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16 views

State of the art in voice recognition

In the media there's lot of talk about face recognition, mainly with respect to identifying faces (= assigning to persons). Less attention is paid to the recognition of facially expressed emotions but ...
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1answer
71 views

Which deep learning models are suitable for image-to-image mapping?

I am working on a problem in which I need to train a neural network to map one or more input images to one or more output images (1 channel for image). Below I report some examples of input&output....

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