Peter Peer

University of Ljubljana · Faculty of Computer and Information Science

>>> Springer Nature SharedIt initiative publicly shares a full-text view-only version of the paper by using the link https://rdcu.be/Os7a! >>> Ear recognition technology has long been dominated by (local) descriptor-based techniques due to their formidable recognition performance and robustness to various sources of image variability. While deep-le...

Image and video data are today being shared between government entities and other relevant stakeholders on a regular basis and require careful handling of the personal information contained therein. A popular approach to ensure privacy protection in such data is the use of deidentification techniques, which aim at concealing the identity of individ...

Automatic identity recognition from ear images represents an active field of research within the biometric community. The ability to capture ear images from a distance and in a covert manner makes the technology an appealing choice for surveillance and security applications as well as other application domains. Significant contributions have been m...

Computer vision is one out of many areas that want to understand the process of human functionality and copy that process with intention to complement human life with intelligent machines. For better human--computer interaction it is necessary for the machine to see people. This can be achieved by employing face detection algorithms, like the one u...

In this paper we present a panoramic depth imaging system. The system is mosaic-based which means that we use a single rotating camera and assemble the captured images in a mosaic. Due to a setoff of the camera's optical center from the rotational center of the system we are able to capture the motion parallax effect which enables stereo reconstruc...

State-of-the-art Face Recognition (FR) models perform well in constrained scenarios, but frequently fail in difficult real-world scenarios, when no quality guarantees can be made for face samples. For this reason, Face Image Quality Assessment (FIQA) techniques are often used by FR systems, to provide quality estimates of captured face samples. The...

Recent developments in deep generative models have opened up a wide range of opportunities for image synthesis, leading to significant changes in various creative fields, including the fashion industry. While numerous methods have been proposed to benefit buyers, particularly in virtual try-on applications, there has been relatively less focus on f...

Modern face recognition and segmentation systems, such as all deep learning approaches, rely on large-scale annotated datasets to achieve competitive performance. However, gathering biometric data often raises privacy concerns and presents a labor-intensive and time-consuming task. Researchers are currently also exploring the use of multispectral d...

This work presents the objectives, methodologies, and preliminary outcomes of the first training activity (TA1) within the AIM@VET project, an EU initiative aimed at integrating artificial intelligence (AI) into vocational education and training (VET) to align with labor market demands. Addressing the noticeable gap in AI education across various e...

In recent years, there has been increasing interest in the conversion of images into audio descriptions. This is a field that lies at the intersection of Computer Vision (CV) and Natural Language Processing (NLP), and it involves various tasks, including creating textual descriptions of images and converting them directly into auditory representati...

V članku predstavimo postopke in tehnike generiranja globoko ponarejenih videoposnetkov ali krajše globokih ponaredkov (angl. deepfakes). To so videoposnetki, pri katerih je prišlo do manipulacij s tehnikami globokega učenja. Taki videoposnetki predstavljajo velik problem pri širjenju lažnih novic, politični propagandi, uničevanju podobe posameznik...

Rapidly advancing development of artificial intelligence technologies, including deep learning techniques in the field of computer vision, has encouraged the need for early education about artificial intelligence in schools. This paper briefly describes the development of a computer vision curriculum, part of the AIM@VET (Artificial Intelligence Mo...

Rubikova kocka je ena najbolj znanih igrač, tako za mlade kot tudi za starejše ljudi. Za začetnike je precej velik zalogaj, zato smo se odločili narediti aplikacijo, ki jo novincem pomaga rešiti. Primarno namen same aplikacije ni učenje reševanja Rubikove kocke, saj se uporabnik z njeno uporabo ne uči, temveč samo dela gibe, ki jih aplikacija pokaž...

The study investigates the task of authorship attribution on short texts in Slovenian using the BERT language model. Authorship attribution is the task of attributing a written text to its author, frequently using stylometry or computational techniques. We create five custom datasets for different numbers of included text authors and fine-tune two...

In the era of rapid digitalization and artificial intelligence advancements, the development of DeepFake technology has posed significant security and privacy concerns. This paper presents an effective measure to assess the visual realism of DeepFake videos. We utilize an ensemble of two Convolutional Neural Network (CNN) models: Eva and ConvNext....

The sclera has recently been gaining attention as a biometric modality due to its various desirable characteristics. A key step in any type of ocular biometric recognition, including sclera recognition, is the segmentation of the relevant part(s) of the eye. However, the high computational complexity of the (deep) segmentation models used in this t...

Modern face recognition (FR) models excel in constrained scenarios, but often suffer from decreased performance when deployed in unconstrained (real-world) environments due to uncertainties surrounding the quality of the captured facial data. Face image quality assessment (FIQA) techniques aim to mitigate these performance degradations by providing...

The microscopic view of blood sample examined under a microscope is termed as microscopy images. The visual quality of such images is not so reassuring due to its acquisition via lens of the microscope. Contrast Limited Adaptive Histogram Equalization (CLAHE) has been useful for improving the visibility of foggy images; the contrast enhancement and...

Gaze estimation is an established research problem in computer vision. It has various applications in real life, from human–computer interactions to health care and virtual reality, making it more viable for the research community. Due to the significant success of deep learning techniques in other computer vision tasks—for example, image classific...

The assessment of fingermark (latent fingerprint) quality is an intrinsic part of a forensic investigation. The fingermark quality indicates the value and utility of the trace evidence recovered from the crime scene in the course of a forensic investigation; it determines how the evidence will be processed, and it correlates with the probability of...

There is an obvious lack of focus on Artificial Intelligence (AI) in multiple levels of education. The paper presents and is a part of the ongoing EU project AIM@VET (Artificial Intelligence Modules for Vocational Education and Training) that covers the development of learning modules aimed at adapting Vocational Education and Training to the needs...

Ear images have been shown to be a reliable modality for biometric recognition with desirable characteristics, such as high universality, distinctiveness, measurability and permanence. While a considerable amount of research has been directed towards ear recognition techniques, the problem of ear alignment is still under‐explored in the open litera...

Kinship face synthesis is an increasingly popular topic within the computer vision community, particularly the task of predicting the child appearance using parental images. Previous work has been limited in terms of model capacity and inadequate training data, which comprised of low-resolution and tightly cropped images, leading to lower synthesis...

Soft–biometric privacy–enhancing techniques represent machine learning methods that aim to: (i) mitigate privacy concerns associated with face recognition technology by suppressing selected soft–biometric attributes in facial images (e.g., gender, age, ethnicity) and (ii) make unsolicited extraction of sensitive personal information infeasible. Bec...

Presents research works in intelligent data engineering and analytics Provides results of FICTA 2023 held at Cardiff Metropolitan University, UK Serves as a reference for researchers and practitioners in academia and industry

Body segmentation is an important step in many computer vision problems involving human images and one of the key components that affects the performance of all downstream tasks. Several prior works have approached this problem using a multi-task model that exploits correlations between different tasks to improve segmentation performance. Based on...

Image-based virtual try-on techniques have shown great promise for enhancing the user-experience and improving customer satisfaction on fashion-oriented e-commerce platforms. However, existing techniques are currently still limited in the quality of the try-on results they are able to produce from input images of diverse characteristics. In this wo...

Recent state-of-the-art face recognition (FR) approaches have achieved impressive performance, yet unconstrained face recognition still represents an open problem. Face image quality assessment (FIQA) approaches aim to estimate the quality of the input samples that can help provide information on the confidence of the recognition decision and event...

Modern deepfake detectors have achieved encouraging results, when training and test images are drawn from the same collection. However, when applying these detectors to faces manipulated using an unknown technique, considerable performance drops are typically observed. In this work, we propose a novel deepfake detector, called SeeABLE, that formali...

Soft-biometric privacy-enhancing techniques represent machine learning methods that aim to: (i) mitigate privacy concerns associated with face recognition technology by suppressing selected soft-biometric attributes in facial images (e.g., gender, age, ethnicity) and (ii) make unsolicited extraction of sensitive personal information infeasible. Bec...

CVPR 2023 paper - We present GlassesGAN, a novel image editing framework for custom design of glasses, that sets a new standard in terms of image quality, edit realism, and continuous multi-style edit capability. To facilitate the editing process with GlassesGAN, we propose a Targeted Subspace Modelling (TSM) procedure that, based on a novel mechan...

Current state-of-the-art segmentation techniques for ocular images are critically dependent on large-scale annotated datasets, which are labor-intensive to gather and often raise privacy concerns. In this paper, we present a novel framework, called BiOcularGAN, capable of generating synthetic large-scale datasets of photorealistic (visible light an...

We introduce a new method to reconstruct 3D objects using a set of volumetric primitives, i.e., superquadrics. The method hierarchically decomposes a target 3D object into pairs of superquadrics recovering finer and finer details. While such hierarchical methods have been studied before, we introduce a new way of splitting the object space using on...

Ocena kakovosti je pomemben korak za identifikacijo prstnih sledi s kraja zločina. Pogosto se izvaja v okviru forenzične preiskave, izvajajo pa ga usposobljeni preiskovalci in je ponavadi precej subjektiven. Cilj našega dela je razviti avtomatizirano metodo ocenjevanja kakovosti prstnih sledi, ki bi pomagala izpraševalcem pri njihovem delu. V tem d...

This paper presents a summary of the Competition on Face Morphing Attack Detection Based on Privacy-aware Synthetic Training Data (SYN-MAD) held at the 2022 International Joint Conference on Biometrics (IJCB 2022). The competition attracted a total of 12 participating teams, both from academia and industry and present in 11 different countries. In...

The task of reconstructing 3D scenes based on visual data represents a longstanding problem in computer vision. Common reconstruction approaches rely on the use of multiple volumetric primitives to describe complex objects. Superquadrics (a class of volumetric primitives) have shown great promise due to their ability to describe various shapes with...

Images of morphed faces pose a serious threat to face recognition--based security systems, as they can be used to illegally verify the identity of multiple people with a single morphed image. Modern detection algorithms learn to identify such morphing attacks using authentic images of real individuals. This approach raises various privacy concerns...

Current state-of-the-art segmentation techniques for ocular images are critically dependent on large-scale annotated datasets, which are labor-intensive to gather and often raise privacy concerns. In this paper, we present a novel framework, called BiOcularGAN, capable of generating synthetic large-scale datasets of photorealistic (visible light an...

The quality assessment of fingermarks (latent fingerprints) is an essential part of a forensic investigation. It indicates how valuable the fingermarks are as forensic evidence, it determines how they should be further processed, and it correlates with the likelihood of successful identification, i.e., finding a matching fingerprint in a reference...

Segmentacija je pomemben del številnih problemov računalniškega vida, ki vključujejo človeške podobe, in je ena ključnih komponent, ki vpliva na uspešnost vseh nadaljnjih nalog. Več predhodnih del je ta problem obravnavalo z uporabo večciljnega modela, ki izkorišča korelacije med različnimi nalogami za izboljšanje uspešnosti segmentacije. Na podlag...

V zadnjem desetletju se je v Laboratoriju za računalniški vid na FRI UL oblikovala močna skupina, ki dela na področju biometrije. Skupina je močno povezana z Laboratorijem za strojno inteligenco na FE UL. Prvi ključni koraki so bili narejeni v okviru kompetenčnih centrov, kjer smo v oblaku naredili fuzijo modalnosti, obrazov in prstih odtisov. Vzpo...

With the proliferation of facial analytics and automatic recognition technology that can automatically extract a broad range of attributes from facial images, so-called soft-biometric privacy-enhancing techniques have seen increased interest from the computer vision community recently. Such techniques aim to suppress information on certain soft-bio...

Crowd counting has a range of applications and it is an important task that can help with the accident prevention such as crowd crushes and stampedes in political protests, concerts, sports, and other social events. Many crown counting approaches have been proposed in the recent years. In this paper we compare five deep-learning-based approaches to...

Bias and fairness of biometric algorithms have been key topics of research in recent years, mainly due to the societal, legal and ethical implications of potentially unfair decisions made by automated decision-making models. A considerable amount of work has been done on this topic across different biometric modalities, aiming at better understandi...

V strokovni literaturi se vse pogosteje pojavljajo potrebe po metodah za zagotavljanje zasebnosti v slikovnih podatkih. Na področju analize obrazov so raziskovalci predlagali metode, ki preslikajo sliko obraza tako, da je samodejno luščenje mehkih biometričnih lastnosti oteženo, obenem pa je vizualni videz slike podoben izvirni sliki. V tem članku...

V strokovni literaturi se vse pogosteje pojavljajo potrebe po metodah za zagotavljanje zasebnosti v slikovnih podatkih. Na področju analize obrazov so raziskovalci predlagali metode, ki preslikajo sliko obraza tako, da je samodejno luščenje mehkih biometričnih lastnosti oteženo, obenem pa je vizualni videz slike podoben izvirni sliki. V tem članku...

For iris recognition in non-cooperative environments, iris segmentation has been regarded as the first most important challenge still open to the biometric community, affecting all downstream tasks from normalization to recognition. In recent years, deep learning technologies have gained significant popularity among various computer vision tasks an...

Biometric recognition technology has made significant advances over the last decade and is now used across a number of services and applications. However, this widespread deployment has also resulted in privacy concerns and evolving societal expectations about the appropriate use of the technology. For example, the ability to automatically extract...

The new Coronavirus disease (COVID-19) has seriously affected the world. By the end of November 2020, the global number of new coronavirus cases had already exceeded 60 million and the number of deaths 1,410,378 according to information from the World Health Organization (WHO). To limit the spread of the disease, mandatory face-mask rules are now b...

Many of the technological advances we enjoy today have been inspired by biological systems due to their ease of operation and outstanding efficiency. Designing technological solutions based on biological inspiration has become a cornerstone of research in a variety of areas ranging from control theory and optimization to computer vision, machine le...

Ear detection represents one of the key components of contemporary ear recognition systems. While significant progress has been made in the area of ear detection over recent years, most of the improvements are direct results of advances in the field of visual object detection. Only a limited number of techniques presented in the literature are doma...

Prepoznava ljudi je temeljni problem, s katerim se ukvarja področje biometrije. V našem delu se ukvarjamo s prepoznavo beločničnih žilnih struktur, ki imajo številne prednosti pred ostalimi značilkami: beločnične žile so edinstvene, tudi med identičnimi dvojčki – celo bolj kot prstni odtisi; za zajem ne potrebujemo posebnih naprav, le običajen foto...

Prepoznava ljudi je temeljni problem, s katerim se ukvarja področje biometrije. V našem delu se ukvarjamo s prepoznavo beločničnih žilnih struktur, ki imajo številne prednosti pred ostalimi značilkami: beločnične žile so edinstvene, tudi med identičnimi dvojčki – celo bolj kot prstni odtisi; za zajem ne potrebujemo posebnih naprav, le običajen foto...