Questions tagged [object-recognition]

For questions related to object recognition, which is the problem of determining the type/class/category of an object in the image, so object recognition could also be called object classification. This is different from object detection, which is either used to refer to object localization (i.e. find the coordinates of the object in the image) + object classification, or just object localization.

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Would Google's self-driving-car stop when it sees somebody with a T-shirt with a stop sign printed on it?

In Hidden Obstacles for Google’s Self-Driving Cars article we can read that: Google’s cars can detect and respond to stop signs that aren’t on its map, a feature that was introduced to deal with ...
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10 votes
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Extending FaceNet’s triplet loss to object recognition

FaceNet uses a novel loss metric (triplet loss) to train a model to output embeddings (128-D from the paper), such that any two faces of the same identity will have a small Euclidean distance, and ...
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6 votes
2 answers
417 views

Can one use an Artificial Neural Network to determine the size of an object in a photograph?

My question relates to but doesn't duplicate a question that has been asked here. I've Googled a lot for an answer to the question: Can you find the dimensions of an object in a photo if you don't ...
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6 votes
1 answer
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How to detect LEGO bricks by using a deep learning approach?

In my thesis I dealt with the question how a computer can recognize LEGO bricks. With multiple object detection, I chose a deep learning approach. I also looked at an existing training set of LEGO ...
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6 votes
1 answer
269 views

What will happen when you place a fake speedsign on a highway?

I was wondering what will happen when somebody places a fake speedsign, of 10 miles per hour on a high way. Will a autonomous car slow down? Is this a current issue of autonomous cars?
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6 votes
2 answers
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Are there any pretrained models for human recognition from all angles?

I need to be able to detect and track humans from all angles, especially above. There are, obviously, quite a few well-studied models for human detection and tracking, usually as part of general-...
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  • 161
5 votes
4 answers
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What could an oscillating training loss curve represent?

I tried to create a simple model that receives an $80 \times 130$ pixel image. I only had 35 images and 10 test images. I trained this model for a binary classification task. The architecture of the ...
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5 votes
2 answers
122 views

Can translational invariance of CNNs be unwanted if object is likely in certain positions?

Various texts on using CNNs for object detection in images talk about how their translation invariance is a good thing. Which makes sense for tasks where the object could be anywhere in the image. Let'...
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5 votes
1 answer
717 views

Precise localization and characterization of rudimentary shapes with neural networks

I understand that there are flavors of (convolutional) neural networks that are useful for object localization and detection tasks of reasonable difficulty. In all of the examples I have seen so far, ...
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5 votes
1 answer
198 views

Why object detection algorithms are poor in optical character recognition?

OCR is still a very hard problem. We don't have universal powerful solutions. We use the CTC loss function An Intuitive Explanation of Connectionist Temporal Classification | Towards Data Science ...
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5 votes
1 answer
656 views

In YOLO, when is $\mathbb{1}_{i j}^{\mathrm{obj}} = 1$, and what are the ground-truth labels for $x_i$ and $y_i$?

I'm trying to implement a custom version of the YOLO neural network. Originally, it was described in the paper You Only Look Once: Unified, Real-Time Object Detection (2016). I have some problems ...
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What are the ways to calculate the error rate of a deep Convolutional Neural Network, when the network produces different results using the same data?

I am new to the object recognition community. Here I am asking about the broadly accepted ways to calculate the error rate of a deep CNN when the network produces different results using the same data....
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4 votes
1 answer
1k views

What is the difference between pixel-based object recognition and feature-based object recognition?

From my understanding and text I found in research papers online : Pixel-based object recognition: neural networks are trained to locate individual objects based directly on pixel data. Feature-based ...
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4 votes
1 answer
166 views

What are some techniques/method that can be used to train and detect objects like cars and humans?

I have used OpenCV to train Haar cascades to detect face and other patterns. However I later realized that Haar tends to give a lot of false positives and I learned of Hog would give a more accurate ...
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  • 149
4 votes
1 answer
55 views

Are there methods that allow deep networks to learn object categorization in a self-supervised way?

When training a deep network to learn object classification from a set like ImageNet, we minimize the cross entropy between the ground truth and the predicted categories. This is done in a supervised ...
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4 votes
1 answer
437 views

How data augmentation like rotation affects the quality of detection?

I'm using an object detection neural network and I employ data augmentation to increase a little my small dataset. More specifically I do rotation, translation, mirroring and rescaling. I notice that ...
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4 votes
2 answers
93 views

How to know whether the object is moving after it is being detected?

If my algorithm detects the type of object, how should I know if that object is moving or not? Suppose a person carrying an umbrella. How to know that the umbrella is moving? I am working on a ...
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  • 149
3 votes
1 answer
172 views

Is there any computer vision technology that can detect any type of object?

Is there any computer vision technology that can detect any type of object? For example, there is a camera fixed, looking in one direction always looking at a similar background. If there is an object,...
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3 votes
1 answer
271 views

Why does the classifier network in RPN output two scores?

The region proposal network (RPN) in Faster-RCNN models contains a classifier and a regressor network. Why does the classifier network output two scores (object and background) for each anchor instead ...
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  • 133
3 votes
1 answer
1k views

How to detect the empty parking spots?

I have some images of the empty parking as shown below. I 'd like to use deep learning to extract the parking spots. But in the beginning,am confused whether there are several ways to do the ...
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3 votes
2 answers
2k views

Which model should I use to find (only) the object location (in terms of coordinates) in an image?

I am generating images that consist of points, where the object's location is where the most overlap of points occurs. In this example, the object location is $(25, 51)$. I am trying to train a model ...
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3 votes
1 answer
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Training a CNN from scratch over COCO dataset [closed]

I am using Tensorflow Object Detection API for training a CNN from scratch on COCO dataset. I need to use this specific configuration. There is no pre-trained model on COCO with that configuration and ...
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3 votes
1 answer
168 views

How to keep track of the same person detected in different frames of a camera?

At this moment, I am able to use NN to identify an object, such as a human, when given a frame from the camera. Once locate the object, then I can feed the human object image to either NN that's ...
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  • 164
3 votes
1 answer
3k views

Identifying cars using deep learning

I would like to use deep leaning for identifying cars; I want the system to predict wether an object is a car or not. How can I do that knowing that im still a beginner in the Deep Learning field ? I ...
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  • 167
3 votes
0 answers
43 views

How are Ground truth provided to each Pyramid map in RetinaNet or YOLOv3 Paper? How is the mapping of Feature Pyramids done to Ground Truth

SO the YOLO V3 and RetinaNet both uses the Feature pyramids which look something like this: (except b and e which have one ...
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  • 233
3 votes
0 answers
58 views

Image classification - Need method to classify "unknown" objects as "trash" (3D objects)

We have an image classifier that was built using CNN with faster R-CNN and Yolov5. It is designated to run on 3D objects. All of those objects have similar "features" structure, but the ...
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3 votes
0 answers
32 views

If random rotations are included in the data augmentation process, how are the new bounding boxes calculated?

When studying bounding box-based detectors, it's not clear to me if data augmentation includes adding random rotations. If random rotations are added, how is the new bounding box calculated?
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3 votes
0 answers
44 views

Video recognition (specifically video, not individual frames)

There are libraries for recognizing individual video frames, but I need to recognize an object in motion. I can recognize a person in every single frame, but I need to know if the person is running or ...
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3 votes
4 answers
455 views

Can bounding boxes further improve the performance of a CNN classifier?

Suppose I have a standard image classification problem (i.e. CNN is shown a single image and predicts a single classification for it). If I were to use bounding boxes to surround the target image (i.e....
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  • 183
3 votes
2 answers
596 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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3 votes
0 answers
627 views

Getting worse performance when training a pre-trained model with the existing class

I am training pre-trained SSD-InceptionV2-Coco to detect the "car", which is one of the classes in mscoco label. I train the model with ~50k sample from KITTI, 500k iteration with batch size 2. I ...
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2 votes
3 answers
3k views

Small size datasets for object detection, segmentation and localization [closed]

I am looking for a small size dataset on which I can implement object detection, object segmentation and object localization. Can anyone suggest me a dataset less than 5GB? Or do I need to know ...
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2 votes
3 answers
115 views

What would the commercial application of a conscious AI look like/be?

Sometimes, but not always in the commercialization of technology, there are some low hanging fruits or early applications, I am having trouble coming up with examples of such applications as they ...
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2 votes
1 answer
508 views

How does Google's self-driving car identify pedestrians?

Based on the article Google's self-driving cars can now spot cyclists: Sensors can read hand signals and predict rider's behaviour, Google's self-driving cars can spot cyclists, cars, road signs, ...
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2 votes
1 answer
91 views

Is it possible to train a CNN to predict the dimensions of primitive objects from point clouds?

Is it possible to train a convolutional neural network (CNN) to predict the dimensions of primitive objects such as (spheres, cylinders, cuboids, etc.) from point clouds? The input to the CNN will be ...
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2 votes
1 answer
43 views

Which API can I use for tracking the position of animal in one or more images?

I'd like to build an application for tracking the position of a given animal (e.g. a cat) in a series of images. Is there any off-the-shelf API I could use? Azure has some Vision APIs, but it seems ...
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2 votes
2 answers
685 views

Is the choice of the optimiser relevant when doing object detection?

Suppose that we have 4 types of dogs that we want to detect (Golden Retriever, Black Labrador, Cocker Spaniel, and Pit Bull). The training data consists of png images of a data set of dogs along with ...
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2 votes
1 answer
42 views

Recognize carp and give them a unique id

For my internship assignment I have to implement a proof of concept for an application that is supposed to scan a picture with a carp on it and identify which carp this is. All of the carps that are ...
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2 votes
1 answer
211 views

Is there any other rotated object detection datasets?

I have googled for a long time for rotated object detection datasets. Most of papers focused on rotated object detection using DOTA, HRSC2016 or coco text detection dataset. Some researcher also ...
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2 votes
1 answer
2k views

How do I detect similar objects in an image?

I want to tackle the problem of detecting similar objects in an image. To illustrate the problem consider this photo of some Lego bricks as my "input": The detection routine should identify similar ...
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  • 121
2 votes
1 answer
136 views

Understanding a paragraph about object detection with two objects

I was reading this article on detecting rectangles in an image. My doubt is in the part where the model works fine with detecting a single object, but struggles with two rectangles detection. The ...
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2 votes
0 answers
41 views

Is it ok to perform transfer learning with a base model for face recognition to perform one-shot learning for object classification?

I am trying to create a model that is using a one-shot learning approach for a classification task. We do this because we do not have a lot of data and it also seems like a good way to learn this ...
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2 votes
0 answers
32 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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2 votes
0 answers
37 views

YOLO 9000 about Better Stronger

In this paper, YOLO has three features compared to YOLO v1. This question is about Better and Faster. In the Better section, there are many techniques such as Batch Norm, Anchor Box and so on. In the ...
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2 votes
0 answers
45 views

FasterRCNN's RPN network training

I would like to know if my understanding of RPN training is correct, and if never training the RPN on some specific anchor box is bad (i.e if the anchor never sees good nor bad examples). To make my ...
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2 votes
1 answer
102 views

Pose estimation using CNNs on Point clouds

In the case of single shot detection of point clouds, that is the point cloud of an object is taken only from one camera view without any registration. Can a Convolutional Network estimate the 6d pose ...
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2 votes
0 answers
22 views

Can Microsoft's cognitive service find similar person in a set of images without using the face service?

I need to create an application that can detect if a person X entered as an input exists in an image set and return as output all the images in which the person X exists. The problem is that the ...
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2 votes
0 answers
52 views

How should I build an AI that quickly detects falling game assets on screen?

I want to build an AI that plays a simple android game. The game is just a one at a time object falling, some times at an angle. The AI needs to recognize the object and to decide whether to swipe ...
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2 votes
0 answers
77 views

Object size identification and maximum number of classes with convolutional neural networks

I am working on a project that involves using a ConvNet to identify screws. I am able to train from scratch a ConvNet based on the first version of the inception network, but shallower (only 3 ...
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2 votes
0 answers
27 views

Sails size recognition

Is it possible to recognize the height and width of the sails of different kitesurfers and windsurfers taken from public webcams? And show these information on video in real time? Or on screenshots?
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