DESEO: An Active Vision System for Detection Tracking and Recognition

Hernández, Mario; Cabrera, Jesús Hernández; Dominguez, A.; Castrillón-Santana, Modesto; Guerra, Cayetano; Hernández, Daniel; Isern, Juan

doi:10.1007/3-540-49256-9_23

Cited by 13 publications

(10 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…These sequences were obtained with the DESEO system [13]. DESEO is a hardware-software system that can detect and follow people in real time, using motion and/or skin colour information.…”

Section: Methodsmentioning

confidence: 99%

An Incremental Learning Algorithm for Face Recognition

Déniz

Castrillón-Santana

Lorenzo

et al. 2002

Biometric Authentication

Self Cite

View full text Add to dashboard Cite

In face recognition, where high-dimensional representation spaces are generally used, it is very important to take advantage of all the available information. In particular, many labelled facial images will be accumulated while the recognition system is functioning, and due to practical reasons some of them are often discarded. In this paper, we propose an algorithm for using this information. The algorithm has the fundamental characteristic of being incremental. On the other hand, the algorithm makes use of a combination of classification results for the images in the input sequence. Experiments with sequences obtained with a real person detection and tracking system allow us to analyze the performance of the algorithm, as well as its potential improvements.

show abstract

“…These sequences were obtained with the DESEO system [13]. DESEO is a hardware-software system that can detect and follow people in real time, using motion and/or skin colour information.…”

Section: Methodsmentioning

confidence: 99%

An Incremental Learning Algorithm for Face Recognition

Déniz

Castrillón-Santana

Lorenzo

et al. 2002

Biometric Authentication

Self Cite

View full text Add to dashboard Cite

show abstract

“…Basically, the tracker keeps a collection of the most stable views of the target that is updated using an error measure between the different patterns in the collection and the best match area with the active pattern. This technique is described in detail in 36 .…”

Section: Trackermentioning

confidence: 99%

<title>Active vision system integrating fast and slow processes</title>

et al. 1998

View full text Add to dashboard Cite

This paper describes an Active Vision System whose design assumes a distinction between fast or reactive and slow or background processes. Fast processes need to operate in cycles with critical timeouts that may affect system stability. While slow processes, though necessary, do not compromise system stability if its execution is delayed. Based on this simple taxonomy, a control architecture has been proposed and a prototype implemented that is able to track people in real-time with a robotic head while trying to identify the target. In this system, the tracking module is considered as the reactive part of the system while person identification is considered a background task. This demonstrator has been developed using a new generation DSP (TMS320C80) as a specialized coprocessor to deal with fast processes, and a commercial robotic head with a dedicated DSP-based motor controller. These subsystems are hosted by a standard Pentium-Pro PC running Windows NT where slow processes are executed. The flexibility achieved in the design phase and the preliminary results obtained so far seem to validate the approach followed to integrate time-critical and slow tasks on a heterogeneous hardware platform.

show abstract

“…For example, the system presented in [20] uses a single camera to acquire images of a single target in an obstacle-free environment. The one degree-of-freedom camera is continuously rotated so that the target remains at the center of the image.…”

Section: Sensor Planning For Active Facial Recognitionmentioning

confidence: 99%

Active-vision system for multi-target surveillance

Bakhtari¹,

Benhabib²

IEEE International Conference Mechatronics and Automation, 2005

View full text Add to dashboard Cite

This paper presents a novel agent-based method for the dynamic, coordinated selection and positioning of groups of active-vision cameras for the surveillance of multiple object-of-interests as they travel through a cluttered environment with a priori unknown trajectories. The proposed dispatching algorithm has been tested via simulations and implemented on an experimental prototype setup for automated facial recognition. Both analyses have shown that the use of dynamic sensors along with an on-line dispatching algorithm can tangibly improve the performance of a surveillance system.

show abstract

DESEO: An Active Vision System for Detection Tracking and Recognition

Cited by 13 publications

References 15 publications

An Incremental Learning Algorithm for Face Recognition

An Incremental Learning Algorithm for Face Recognition

<title>Active vision system integrating fast and slow processes</title>

Active-vision system for multi-target surveillance

Contact Info

Product

Resources

About