The Smart Sense Laboratory, former Smart Surveillance Interest Group (SSIG), is coordinated by Prof. William Robson Schwartz and composed of researchers, graduate and undergraduate students that investigate problems related to Video Surveillance, Forensics and Biometrics by developing techniques on Computer Vision, Pattern Recognition and Digital Image Processing. The research group tackles problems including feature extraction, background subtraction, pedestrian detection, spoofing detection, person tracking, face recognition, person re-identification, pose estimation, gesture recognition, anomaly detection and activity recognition to allow scene understanding.

The laboratory provides a highly collaborative environment for its members by holding weekly meetings to discuss recent research papers, algorithms and research developments. In addition, the group maintains a computational infrastructure composed of powerful servers, large storage space, GPU cards and multiple surveillance cameras that allows the execution of large-scale experiments.

 

Sense members win 2nd place in the AVSS challenge on Semantic Person Retrieval Using Soft Biometrics

Sense members win 2nd place in the AVSS challenge on Semantic Person Retrieval Using Soft Biometrics

A method proposed by Sense members won 2nd place on the "Surveillance Imagery Search” task of the Semantic Person Retrieval in Surveillance Using Soft Biometrics challenge, at the Conference on Advanced Video and Signal-based Surveillance, AVSS 2018. Gabriel Resende Gonçalves led the work, developed in collaboration with the graduate students Antonio Carlos de Nazare Junior, Matheus Alves Diniz and undergraduate ...
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/ News
Sense graduate Samira Silva wins 2nd place on the Master’s Thesis Award at WVC 2018

Sense graduate Samira Silva wins 2nd place on the Master’s Thesis Award at WVC 2018

Samira Santos da Silva won 2nd place on the Master’s Thesis category of the Thesis and Dissertation Contest of the Workshop on Computer Vision, WVC 2018. Currently, a Professor at the Itaúna University Foundation, the Smart Sense Laboratory’s graduate presented her research Aggregating Partial Least Squares Models for Open-set Face Identification, defended earlier this year. In its 14th edition, ...
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/ News
SSIG-ALPR Database

SSIG-ALPR Database

This dataset, called SSIG-ALPR Database, was created to help researchers evaluating automatic license plate recognition problems. The data for the paper Real-time Automatic License Plate Recognition Through Deep Multi-Task Networks  (link to the research page) were captured during the day using two cameras: one placed static while recording the vehicles that were passing by and another placed within a vehicle ...
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Professor Schwartz presents a talk on person identification in surveillance at WVC 2018

Professor Schwartz presents a talk on person identification in surveillance at WVC 2018

The coordinator of the Smart Sense Laboratory, Professor William Schwartz presented a talk on person identification in surveillance scenarios last Monday (12), at the 14th Workshop on Computer Vision (WVC). The current edition of the WVC takes place on November 12-14, at the State University of Santa Cruz (UESC), Ilhéus, Bahia. Computer vision techniques applied to video surveillance and biometrics ...
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/ News, Person Re-identification
Sense member Rafael Vareto wins Best Master’s Thesis Award at SIBGRAPI 2018

Sense member Rafael Vareto wins Best Master’s Thesis Award at SIBGRAPI 2018

Rafael Henrique Vareto won the Best Master’s Thesis Award on the Workshop of Theses and Dissertations (WTD) of the 31st Conference on Graphics, Patterns and Images, SIBGRAPI 2018. Currently a Ph.D. student, the Sense member presented his research “Face Recognition Based on a Collection of Binary Classifiers”, defended last year. Started on October 29 and ended yesterday, SIBGRAPI is the ...
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/ Face Recognition, News
The Smart Sense Laboratory joins Petrobras in a three-year research and development project

The Smart Sense Laboratory joins Petrobras in a three-year research and development project

The Smart Sense Laboratory has partnered with Petrobras, one of the largest petroleum companies in the world and the largest in Brazil, to work on a three-year R&D project. The main goal is the implementation of an automatic monitoring system for worker protection on oil platforms. The system will be capable of identifying risk situations and issuing alerts to improve ...
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/ Current Projects, News
Sense research arrives in Oceania: Igor Bastos has his work accepted in AVSS 2018

Sense research arrives in Oceania: Igor Bastos has his work accepted in AVSS 2018

Sense Ph.D. student Igor Bastos was selected to present his novel approach for gesture recognition at the 15th IEEE International Conference on Advanced Video and Signal-based Surveillance (AVSS). Sponsored by the Institute of Electrical and Electronics Engineers (IEEE), AVSS 2018 will be held in Auckland, New Zealand, from 27 to 30 November. Due to its applicability in contexts such as ...
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A new master in the group: Jessica Sena defended her dissertation

A new master in the group: Jessica Sena defended her dissertation

Jessica Sena defended this afternoon (18), her dissertation “Human Activity Recognition based on Wearable Sensors using Multiscale DCNN Ensemble”, obtaining her Master’s degree from the Graduate Program in Computer Science of the Federal University of Minas Gerais (UFMG). The main results of her research were presented two months ago at the European Signal Processing Conference (EUSIPCO), in Rome, Italy. Sena ...
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Victor Hugo de Melo will present his research on activity recognition at SIBGRAPI 2018

Victor Hugo de Melo will present his research on activity recognition at SIBGRAPI 2018

Images extracted from the datasets used to train the method. Video understanding is the next frontier of computer vision, in which activity recognition plays a major role. Ph.D. student Victor Hugo Melo will present his new approach to the subject, based on contextual cues obtained from object detections in the scene, at the main conference on computer vision in ...
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Active Cameras

Active Cameras

Unlike fixed cameras, which are limited to a static view of the scene, active cameras are capable of changing their view by means of, for instance, rotation (pan and tilt) and zoom. Cameras with these particular capabilities are known as PTZ (pan-tilt-zoom) cameras, and are widely employed in surveillance for viewing and tracking under dynamic conditions. By shifting to and zooming on ...
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Professor William Schwartz presents a talk on video surveillance and biometrics at UNESP

Professor William Schwartz presents a talk on video surveillance and biometrics at UNESP

This Tuesday (2), the amphitheater of the Faculty of Science and Technology of the Universidade Estadual Paulista (UNESP) hosts a talk by Professor William Schwartz, head of Smart Sense Laboratory, in the 7th Computer Science Week of Presidente Prudente. Closing the activities scheduled for the day, his talk will address the challenges of computer vision in video surveillance and biometrics. ...
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/ News
Activity Recognition based on Wearable Sensors

Activity Recognition based on Wearable Sensors

Human activity recognition based on wearable sensors has received great attention in areas such as healthcare, homeland security and smart environments, mainly because it enables easy data acquisition and processing. This task consists of assigning a category of activity to signals provided by wearable sensors such as accelerometers, gyroscopes and magnetometers. Software Publications ...
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Gabriel Gonçalves will present his new approach for license plate recognition at SIBGRAPI 2018

Gabriel Gonçalves will present his new approach for license plate recognition at SIBGRAPI 2018

An essential task to ensure the identification of vehicles and safety on roads and private spaces, Automatic License Plate Recognition (ALPR) is the research subject of Gabriel Gonçalves, a Ph.D. student at Sense, who will present his work at the Conference on Graphics, Patterns and Images (SIBGRAPI). In its 31st edition, SIBGRAPI is the main conference on computer vision ...
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/ News
Jessica Sena represents the Smart Sense Laboratory at the EUSIPCO conference in Italy

Jessica Sena represents the Smart Sense Laboratory at the EUSIPCO conference in Italy

Last week, Rome was the venue for the 26th edition of the European Signal Processing Conference, EUSIPCO 2018, and Sense’s researcher Jessica Sena was there to present her work on Deep Convolutional Neural Networks (DCNN) applied to human activity recognition based on wearable sensors. The conference, which is currently assigned a Qualis A2 score (the second highest) by the Brazilian ...
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/ News
Researcher Rensso Colque gets Ph.D.'s degree in Computer Science

Researcher Rensso Colque gets Ph.D.’s degree in Computer Science

Rensso Mora Colque obtained this Friday (24) his Ph.D. title by the Graduate Program in Computer Science of the Federal University of Minas Gerais (UFMG). His dissertation, “Robust approaches for anomaly detection applied to video surveillance”, was guided by Sense head, professor William Robson Schwartz and proposed three approaches to detect anomalous patterns in surveillance video sequences. A topic that ...
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/ News
Sense researchers make advances in controlling active cameras

Sense researchers make advances in controlling active cameras

                                              Unlike fixed cameras, statically positioned to better capture a global view of the scene, active cameras or PTZs (pan-tilt-zoom) have a feature that allows them to move on the axis itself in the vertical, horizontal and zoom ...
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/ Active Cameras, Machine Learning, News
SensorCap: Sensor Data Capture

SensorCap: Sensor Data Capture

SensorCap is an Android tool that captures sensor data in user-defined configurations. The purpose is to allow researchers and developers to quickly save sensor data for research, testing and prototyping. The sensors are broadly defined to include "motion", "position" and "environment" device sensors. An intuitive user interface facilitates tasks such as setting up a sensor, entering capture details and sharing ...
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Benchmark on Activity Recognition based on Wearable Sensors

Benchmark on Activity Recognition based on Wearable Sensors

This page contains the source code and data used in our paper "Human Activity Recognition Based on Wearable Sensor Data: A Standardization of the State-of-the-Art". In this paper, we implement and evaluate several state-of-the-art approaches, ranging from methods based on handcrafted features to convolutional neural networks. Also, we standardize a large number of datasets, which vary in terms of sampling rate, ...
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Job opportunity for developers on a project in parnership with Petrobras

Job opportunity for developers on a project in parnership with Petrobras

The SSIG is looking for developers to work on a Research and Development project in partnership with Petrobras S.A. The applicant will work on the development of a distributed, scalable smart video-surveillance system with real-time requirements using cutting-edge technologies to provide a high-performance system able to analyze the scene and provide a secure environment to the workers. We are hiring ...
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/ News
SSIG offers masters scolarship on a project with Petrobras

SSIG offers masters scolarship on a project with Petrobras

The Smart Surveillance Interest Group offers a masters scholarship to work on the problem of active cameras in a large Research and Development project in partnership with Petrobras. The problem with Active Cameras is to control and coordinate a large set of cameras in order to capture visual data with a greater level of detail. For this, computer vision, machine ...
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/ News
OFCM - Optical Flow Co-occurrence Matrices

OFCM – Optical Flow Co-occurrence Matrices

Source code of the spatiotemporal feature descriptor proposed in the Optical Flow Co-occurrence Matrices: A Novel Spatiotemporal Feature Descriptor (ICPR 2016). Aiming at capturing more information from the optical flow, this work proposes a novel spatiotemporal local feature descriptor called Optical Flow Co-occurrence Matrices (OFCM). The method is based on the extraction of Haralick features from co-occurrence matrices computed using the ...
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Best Paper Runner-up Award - IJCB 2017

Best Paper Runner-up Award – IJCB 2017

SSIG paper Towards Open-Set Face Recognition using Hashing Functions received the Best Paper Runner-up Award in the International Joint Conference on Biometrics (IJCB 2017). This paper tackles open-set face identification. The problem of open-set face recognition determines whether the subject’s picture presented to the recognition system belongs to a known individual (person in the gallery). This problem is of great importance to find ...
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/ Face Recognition, News
Importance Annotation for VIP and UIUC Pascal Sentence Datasets

Importance Annotation for VIP and UIUC Pascal Sentence Datasets

The experimental results for the paper Assigning Relative Importance to Scene Elements in SIBGRAPI’2017 (link to the research page) were obtained using two datasets: VIP dataset and UIUC Pascal Sentence. Both datasets are associate to importance assignment researches and present a wide range of images containing multiple objects per image. Data In order to use both datasets on the paper Assigning Relative Importance to Scene Elements, it ...
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/ Datasets, Importance Assignment
Importance Assignment to Scene Elements

Importance Assignment to Scene Elements

The human brain is able to rapidly understand scenes through the recognition of their composing elements and comprehension of the role that each of them plays. This process, related to human perception, impacts in what people care when they see an image and the priority they give to each element. The idea of priority, also referred as importance, is based on biological features of ...
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/ Current Research
R&D Project - Video Analytics Solutions

R&D Project – Video Analytics Solutions

The Smart Surveillance Interest Group started early this month the execution of a R&D project as a partnership with Maxtrack, a Minas Gerais based company leader in vehicle tracking and telemetry, through EMBRAPII DCC/UFMG. The project main focus is the development of algorithms based on computer vision and machine learning for video analytics considering Internet of Things (IoT) scenarios. Several problems in ...
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/ News, Projects
SSAT - Smart Surveillance Annotation Tool

SSAT – Smart Surveillance Annotation Tool

Smart Surveillance Annotation Tool (SSAT), as it own name indicates, is an annotation tool, free and interactive, for the computer vision community. This eases the way researchers and annotation massive video datasets. This tool is still in progress, in the future it will be possible to create and manipulate bounding boxes in the video. Explanatory video Video extracted from Interactive Dataset, CPR contest ...
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/ Annotation Tool, Software
2nd DeepEyes Workshop

2nd DeepEyes Workshop

The 2nd DeepEyes Workshop was held at UFMG Campus in October 03, 2016. Counting with around 70 people, including researchers such as Larry S. Davis (University of Maryland), François Bremond (INRIA), Eduardo Valle (Unicamp), Sandra Ávila, Filipe Costa, William Robson Schwartz (UFMG), were presented and discussed advances achieved in the previous year of the project in problems such as forgery detection on digital ...
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/ News
SSIGLib - Smart Surveillance Interest Group Library

SSIGLib – Smart Surveillance Interest Group Library

The Smart Surveillance Interest Group Library (SSIGLib) is a C/C++ library built to provide a set of functionalities that aid researchers not only on the development of surveillance systems but also on the creation of novel solutions for problems related to video surveillance. The SSIGLib was designed to provide features for a good scene understanding, scalability, real-time operation, multi-sensor environment, ...
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/ Software
Kernel Hierarchical PCA for Person Re-Identification (ICPR 2016)

Kernel Hierarchical PCA for Person Re-Identification (ICPR 2016)

Source code used in the Kernel Hierarchical PCA for Person Re-Identification (ICPR 2016). In this paper, we tackle the person re-identification problem as a common subspace learning and propose a novel framework, which we named Kernel HPCA, that handles with camera transition and dimensionality reduction. Kernel HPCA is a nonlinear extension of Hierarchical PCA (HPCA). HPCA is known in chemometrics as ...
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AVSS2016 unsupervised prid450s

Kernel Partial Least Squares for Person Re-Identification (AVSS 2016)

Source code used in the Kernel Partial Least Squares for Person Re- Identification (AVSS 2016). In this paper, we approach supervised and unsupervised person re-identification (Re-ID) problem in two widely used datasets (VIPER and PRID450S) using Kernel Partial Least Squares. Regarding supervised Re-ID, we present a common subspace learning method, which we coined Kernel PLS Mode A, and a cross-view discriminative ...
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SSIG License Plate Character Segmentation Database

SSIG License Plate Character Segmentation Database

This dataset, called SSIG SegPlate Database, aims at evaluating the License Plate Character Segmentation (LPCS) problem. The experimental results for the paper Benchmark for License Plate Character Segmentation  (link to the research page) were obtained using a dataset providing 101 on-track vehicles captured during the day. The video was recorded using a static camera in the early 2015. Data The images of the dataset were acquired ...
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HOMF Descriptor for Anomalous Pattern Recognition

HOMF Descriptor for Anomalous Pattern Recognition

Source code used in the paper Histograms of Optical Flow Orientation and Magnitude to Detect Anomalous Events in Videos (published on SIBGRAPI 2015). In this paper, we propose the use of magnitude and orientation to describe patterns in crowded scenes. This model describes spatiotemporal regions in the scene to determine if they presents a normal or anomalous pattern.  Our descriptor ...
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/ Feature Extraction, Software
Anomaly Detection Results

Anomaly Detection Results

This page shows results found in the literature for anomalous event detection in crowd data sets. If you like to have your published results added in the following tables, please send an e-mail to Rensso Mora with the link (or the pdf) to your paper and the results to be reported. Up to now, we have tabulated the results for the following datasets ...
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/ Feature Extraction, Results, surveillance
Person Re-identification Results

Person Re-identification Results

This page shows results found in the literature for several person re-idenfication datasets (sort by rank-1 CMC). If you like to have your published results added in the following tables, please send an e-mail to Raphael Prates with the link (or the pdf) to your paper and the results to be reported. Up to now, we have tabulated the results for the following ...
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/ Results
CBRA - Color-Based Ranking Aggregation for Person Re-Identification

CBRA – Color-Based Ranking Aggregation for Person Re-Identification

Source code used in the paper CBRA - Color-Based Ranking Aggregation for Person Re- Identification (ICIP 2015). In this paper, we propose the use of rank aggregation to improve the results, in which we address the person re-identification problem using a Color-based Ranking Aggregation (CBRA) method that explores different feature representations to obtain complementary ranking lists and combine them using the Stuart ranking ...
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ICB 2015 Appearance-Based Person Re-Identification

ICB 2015 Appearance-Based Person Re-Identification

This page contains the Software used on the paper presented in ICB 2015 (Appearance-Based Person Re-Identification by Intra-Camera Discriminative Models and Ranking Aggregation). In this work, we used prototypes to indirectly handle with the camera transition problem. Thus, for a given gallery image, we computed the most similar individuals in training set that were captured by the same camera. For each ...
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Smart Surveillance Framework

Smart Surveillance Framework

The Smart Surveillance Framework is a C/C++ library built using the OpenCV and the C++ Standard Template Library to provide a set of functionalities to aid researchers not only on the development of surveillance systems but also on the creation of novel solutions for problems related to video surveillance. One of its main goals is to provide a set of ...
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/ Software, surveillance
PLS NIPALS C++

PLS NIPALS C++

This library provides a C++ class to execute Partial Least Squares (PLS) NIPALS method for a scalar response variable for both dimension reduction or regression. It provides a class composed of methods to build, load, and store a PLS model, project feature vectors onto the PLS model and retrieve its low dimensional representation. PLS handles data in high dimensional feature ...
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/ Partial Least Squares, Software
Histogram of Shearlet Coefficients (HSC)

Histogram of Shearlet Coefficients (HSC)

This library provides a C++ class called HSC to perform feature extraction using the histogram of shearlet coefficients (HSC), method proposed in the paper A Novel Feature Descriptor Based on the Shearlet Transform (ICIP). Shearlet transforms provide a general framework for analyzing and representing data with anisotropic information at multiple scales. As a consequence, signal singularities, such as edges, can be ...
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/ Feature Extraction, Software
PLS Face Identification

PLS Face Identification

This software, called PLS Face Identification (PFI), implements the one-against-all face identification method proposed in [1] and [2] (the second is an extension of the first by adding new feature descriptors). This software allows researchers to compare face identification methods to our method using datasets other than those considered in our papers. To facilitate its usage, we provide a small data ...
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/ Face Recognition, Software
DetectorPLS

DetectorPLS

DetectorPLS is an implementation of the paper Human Detection Using Partial Least Squares Analysis.W.R. Schwartz, A. Kembhavi, D. Harwood, L. S. Davis. In proceedings of the ICCV. Kyoto, Japan, 2009 [pdf] [project webpage]. The goal of this implementation is to allow researchers to perform detection using already learned models for applications such as human and face detection and also provide a simple way ...
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/ Pedestrian Detection, Software
ETHZ Dataset for Appearance-Based Modeling

ETHZ Dataset for Appearance-Based Modeling

The experimental results for the paper Learning Discriminative Appearance-Based Models Using Partial Least Squares in SIBGRAPI'2009 (link to the research page) were obtained using the ETHZ dataset, which provides a large number of different people captured in uncontrolled conditions. The video sequences are captured from moving cameras, which provides a range of variations in people's appearances. Data We used the ground truth location ...
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/ Datasets, Person Re-identification