Showing 1-25 of 7,255 resultsfor "Index Terms":Action Coding
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MAC With Action-Dependent State Information at One Encoder
The growing interest in action-dependent channels motivates us to extend the study of action-dependent settings, which until now focused on point-to-point models, to multiple-access channels (MACs). In this paper, we consider a two-user, state-dependent MAC, in which one of the encoders, called the informed (cognitive) encoder, is allowed to take an action that affects the formation of the channel...Show More
Information Embedding on Actions
Behzad Ahmadi;Himanshu Asnani;Osvaldo Simeone;Haim H. Permuter
The problem of optimal actuation for channel and source coding was recently formulated and solved in a number of relevant scenarios. In this class of models, actions are taken at encoders or decoders, either to acquire side information in an efficient way or to control or probe effectively the channel state. In this paper, the problem of embedding information on the actions is studied for both the...Show More
Action recognition by Huffman coding and implicit action model
2015 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA)
Year: 2015 | Conference Paper |
Cited by: Papers (1)
Human action recognition is at the core of computer vision, and has great application value in intelligent human-computer interactions. On the basis of Bag-of-Words (BoW), this work presents a Huffman coding and Implicit Action Model (IAM) combined framework for action recognition. Specifically, Huffman coding, which outperforms naïve Bayesian method, is a robust estimation of visual words' condit...Show More
Lossless Coding of Correlated Sources With Actions
This paper studies the problem of the distributed compression of correlated sources with an action-dependent joint distribution. This class of problems is, in fact, an extension of the Slepian-Wolf model, but where cost-constrained actions taken by the encoder or the decoder affect the generation of one of the sources. The purpose of this paper is to study the impact of actions on the achievable r...Show More
CU Size Decision for Low Complexity HEVC Intra Coding based on Deep Reinforcement Learning
2020 IEEE 63rd International Midwest Symposium on Circuits and Systems (MWSCAS)
Year: 2020 | Conference Paper |
Cited by: Papers (5)
High efficiency video coding (HEVC) uses a quadtree-based structure for coding unit (CU) splitting to effectively encode various video sequences with different visual characteristics. However, this new structure results in a dramatically increased complexity that makes real-time HEVC encoding very challenging. In this paper, we propose a novel CU size decision method based on deep reinforcement le...Show More
Coding With Action-Dependent Side Information and Additional Reconstruction Requirements
Kittipong Kittichokechai;Tobias J. Oechtering;Mikael Skoglund
Two classes of source/channel coding problems, namely, coding with action-dependent side information and coding with additional signal reconstruction are considered in a unified fashion. In the source coding setting, a decoder wishes to reconstruct the source subject to a distortion constraint, while an encoder is required to estimate the decoder's reconstruction reliably. Side information is acti...Show More
We present a novel approach to entropy coding, which provides the coding efficiency and simple probability modeling capability of arithmetic coding at the complexity level of Huffman coding. The key element of the proposed approach is a partitioning of the unit interval into a small set of probability intervals. An input sequence of discrete source symbols is mapped to a sequence of binary symbols...Show More
Information embedding on actions
Behzad Ahmadi;Himanshu Asnani;Osvaldo Simeone;Haim H. Permuter
2013 IEEE International Symposium on Information Theory
Year: 2013 | Conference Paper |
Cited by: Papers (6)
The problem of optimal actuation for channel and source coding was recently formulated and solved in a number of relevant scenarios. In this class of models, actions are taken either to acquire side information in an efficient way for source coding, or to control or probe effectively the channel state for channel coding. In this paper, the problem of embedding information on the actions is introdu...Show More
Human action recognition is a challenging and active research area in computer vision. In this paper, we propose a simple yet effective method, called the locality-constrained linear coding (LLC) based two-dimensional spatial-temporal templates, to learn a discriminative representation for human action recognition. Our proposed method calculates twodimensional spatial-temporal templates from each ...Show More
Construction of Polar Codes With Reinforcement Learning
This paper formulates the polar-code construction problem for the successive-cancellation list (SCL) decoder as a maze-traversing game, which can be solved by reinforcement-learning techniques. The proposed method provides a novel technique for polar-code construction that no longer depends on sorting and selecting bit-channels by reliability, as in most current algorithms. Instead, this technique...Show More
Inferring Student Frustration in a Code Reading Exercise Based on Facial Expression
2024 6th International Workshop on Artificial Intelligence and Education (WAIE)
Year: 2024 | Conference Paper |
Frustration plays a crucial role in learning, particularly in programming education, where students often struggle with reading and understanding code. While frustration is commonly viewed as negative, it can also signal active engagement with challenging tasks. This study aims to detect student frustration through facial expressions during code-reading exercises. An experiment collected video rec...Show More
Facial Emotion Prediction through Action Units and Deep Learning
2020 2nd International Conference on Advancements in Computing (ICAC)
Year: 2020 | Conference Paper |
Cited by: Papers (8)
With the recent advancements in deep learning techniques, attention has been given to training and testing facial emotions through highly complex deep learning systems. In this paper we apply machine learning techniques which require less resources to produce comparable results for emotion prediction. As the underlying technique for the emotion prediction in this research is based on clinically re...Show More
We consider the setting where actions can be used to modify a state sequence before compression. The minimum rate needed to losslessly describe the optimal modified sequence is characterized when the state sequence is either noncausally or causally available at the action encoder. The achievability is closely related to the optimal channel coding strategy for channel with states. We also extend th...Show More
Hierarchical NeuroSymbolic Approach for Comprehensive and Explainable Action Quality Assessment
2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
Year: 2024 | Conference Paper |
Action quality assessment (AQA) applies computer vision to quantitatively assess the performance or execution of a human action. Current AQA approaches are end-to-end neural models, which lack transparency and tend to be biased because they are trained on subjective human judgements as ground-truth. To address these issues, we introduce a neuro-symbolic paradigm for AQA, which uses neural networks...Show More
Correlated sources with actions
2013 51st Annual Allerton Conference on Communication, Control, and Computing (Allerton)
Year: 2013 | Conference Paper |
In this paper, we consider the problem of distributed compression of correlated sources with action-dependent joint distribution. This setup is an extension of the Slepian Wolf model, but where actions taken by the encoder or the decoder and affect the generation of one of the sources. In both cases, we characterize the set of achievable rates completely, and show how the actions in the system aff...Show More
Enumeration of Extended Irreducible Binary Goppa Codes
The family of Goppa codes is one of the most interesting subclasses of linear codes. As the McEliece cryptosystem often chooses a random Goppa code as its key, knowledge of the number of inequivalent Goppa codes for fixed parameters may facilitate in the evaluation of the security of such a cryptosystem. In this paper we present a new approach to give an upper bound on the number of inequivalent e...Show More
Orbit Structure of Grassmannian G2,m and a Decoder for Grassmann Code C(2, m)
In this article, we consider decoding Grassmann codes, linear codes associated to the Grassmannian and its embedding in a projective space. We look at the orbit structure of Grassmannian arising from the multiplicative group ${\mathbb {F}}_{q^{m}}^{*}$ in $GL_{m}(q)$ . We project the corresponding Grassmann code onto these orbits to obtain a subcode of a $q$ –ary Reed-Solomon code. We prove th...Show More
Improved Non-Uniform Constellations for Non-Binary Codes Through Deep Reinforcement Learning
2022 IEEE 23rd International Workshop on Signal Processing Advances in Wireless Communication (SPAWC)
Year: 2022 | Conference Paper |
Cited by: Papers (1)
Non-binary forward error correction (FEC) codes have been getting more attention lately in the coding society thanks mainly to their improved error correcting capabilities. Indeed, they reveal their full potential in the case of a one-to-one mapping between the code symbols over Galois fields (GF) and constellation points of the same order. Previously, we proposed non-binary FEC code designs targe...Show More
Human Action Recognition Based on Image Coding and CNN
2022 IEEE 4th Eurasia Conference on IOT, Communication and Engineering (ECICE)
Year: 2022 | Conference Paper |
In human action recognition, the way of collecting action data through video or photos is easily affected by factors such as perspective and light, and it is not easy to describe and extract features. To solve this problem, we researched human skeletal joint data and the use of the convolutional neural network (CNN). The joint data was converted into a PNG image by image coding. In addition, we pr...Show More
Human Action Recognition and Coding based on Skeleton Data for Visually Impaired and Blind People Aid System
2022 First International Conference on Computer Communications and Intelligent Systems (I3CIS)
Year: 2022 | Conference Paper |
Cited by: Papers (3)
This work aims to contribute to the development of a novel device, perceivable by the touch sense, that allows visually impaired and blind persons understand the actions of the people around them. Therefore, we propose an end-to-end system that takes skeleton data, captured by kinect sensor, as input data and recognizes the performed human actions in the surrounding scene using a state-of-the-art ...Show More
If we want to recognize the emotion via the face-to face interaction, first of all, we need to extract the emotional features from the facial image by using a feature extraction method. The active appearance model (AAM) is a well-known method that can represent a non-rigid object, such as face, facial expression regions as emotional features. And then we need to classify the emotional status relia...Show More
Action Potential Detection Algorithm Adaptable to Individual Nerve and Recording Setup
Romain Raffoul;Javier Chávez Cerda;Elena Acedo Reina;Hugo Smets;Maxime Verstraeten;Louis Vande Perre;Rami Taheri;Pascal Doguet;Jean Delbeke;Riëm El Tahry;Jacques Deviere;Antoine Nonclercq
2022 IEEE Biomedical Circuits and Systems Conference (BioCAS)
Year: 2022 | Conference Paper |
Cited by: Papers (5)
This work presents an automated analysis algorithm to detect action potentials (APs) in a nerve and quantify its activity. The algorithm is based on template matching. The templates are automatically adapted to individual AP shapes that vary depending on the nerve fibers from which the AP originates, and the recording setup used. The algorithm was validated by quantifying vagus nerve activity reco...Show More
Action Potential Detection Algorithm Adaptable to Individual Nerve and Recording Setup
Romain Raffoul;Javier Chávez Cerda;Elena Acedo Reina;Hugo Smets;Maxime Verstraeten;Louis Vande Perre;Rami Taheri;Pascal Doguet;Jean Delbeke;Riëm El Tahry;Jacques Deviere;Antoine Nonclercq
Year: 2022 | Conference Paper |
Sparse coding-based spatiotemporal saliency for action recognition
2015 IEEE International Conference on Image Processing (ICIP)
Year: 2015 | Conference Paper |
Cited by: Papers (6)
In this paper, we address the problem of human action recognition by representing image sequences as a sparse collection of patch-level spatiotemporal events that are salient in both space and time domain. Our method uses a multi-scale volumetric representation of video and adaptively selects an optimal space-time scale under which the saliency of a patch is most significant. The input image seque...Show More
HapFACS 3.0: FACS-Based Facial Expression Generator for 3D Speaking Virtual Characters
With the growing number of researchers interested in modeling the inner workings of affective social intelligence, the need for tools to easily model its associated expressions has emerged. The goal of this article is two-fold: 1) we describe HapFACS, a free software and API that we developed to provide the affective computing community with a resource that produces static and dynamic facial expre...Show More
New Characterization and Parametrization of LCD Codes
Linear complementary dual (LCD) cyclic codes were referred historically to as reversible cyclic codes, which had applications in data storage. Due to a newly discovered application in cryptography, there has been renewed interest in LCD codes. In particular, it has been shown that binary LCD codes play an important role in implementations against side-channel attacks and fault injection attacks. I...Show More
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