ENCARA2: Real-time detection of multiple faces at different resolutions in video streams

Castrillón, Modesto; Déniz, Óscar; Guerra, Cayetano; Hernández, Mario

doi:10.1016/j.jvcir.2006.11.004

Cited by 167 publications

(81 citation statements)

References 27 publications

(41 reference statements)

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“…Speed is the main goal in our application, and the face detector is critical for the live-video selector. More details of ENCARA2 can be found in Castrillón et al (2007).…”

Section: Methodsmentioning

confidence: 99%

“…To test the effect of homeostatic regulation in the Castrillón et al (2007). TD: correct detection ratio; FD: false detection ratio face detection task, a performance measure was defined as the ratio between the number of detected faces in a second and the number of images per second.…”

Section: Methodsmentioning

confidence: 99%

“…Cue combination usually provides greater robustness and higher processing speeds, particularly for live video stream processing. This is evidenced by the fact that a face detector based on cue combination (Castrillón et al, 2007) outperforms single cue based detectors (Viola and Jones, 2004), providing a more reliable tool for real-time interaction.…”

Section: Face and Eye Detectionmentioning

confidence: 99%

“…The face detection system developed for the selector (called ENCARA2, see Castrillón et al (2007) for details) integrates, among other cues, different classifiers based on the general object detection framework by Viola and Jones (2004): skin color, multi-level tracking, etc. The detection system provides not only face detection but also eye location in many situations.…”

Section: Face and Eye Detectionmentioning

confidence: 99%

See 3 more Smart Citations

Computer vision based eyewear selector

Déniz

Castrillón

Lorenzo

et al. 2010

J. Zhejiang Univ. - Sci. C

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Abstract:The widespread availability of portable computing power and inexpensive digital cameras are opening up new possibilities for retailers in some markets. One example is in optical shops, where a number of systems exist that facilitate eyeglasses selection. These systems are now more necessary as the market is saturated with an increasingly complex array of lenses, frames, coatings, tints, photochromic and polarizing treatments, etc. Research challenges encompass Computer Vision, Multimedia and Human-Computer Interaction. Cost factors are also of importance for widespread product acceptance. This paper describes a low-cost system that allows the user to visualize different glasses models in live video. The user can also move the glasses to adjust its position on the face. The system, which runs at 9.5 frames/s on general-purpose hardware, has a homeostatic module that keeps image parameters controlled. This is achieved by using a camera with motorized zoom, iris, white balance, etc. This feature can be specially useful in environments with changing illumination and shadows, like in an optical shop. The system also includes a face and eye detection module and a glasses management module.

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“…Speed is the main goal in our application, and the face detector is critical for the live-video selector. More details of ENCARA2 can be found in Castrillón et al (2007).…”

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Face and Eye Detectionmentioning

confidence: 99%

Section: Face and Eye Detectionmentioning

confidence: 99%

See 2 more Smart Citations

Computer vision based eyewear selector

Déniz

Castrillón

Lorenzo

et al. 2010

J. Zhejiang Univ. - Sci. C

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show abstract

“…The face detection system used for this work (see [3]) integrates, among other cues, different classifiers based on the general object detection framework by Viola and Jones [4], skin color, multilevel tracking, etc.…”

Section: Face Detectionmentioning

confidence: 99%

Smile Detection for User Interfaces

Deniz

Castrillón

Lorenzo

et al. 2008

Advances in Visual Computing

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Abstract. Perceptual User Interfaces (PUIs) aim at facilitating humancomputer interaction with the aid of human-like capacities (computer vision, speech recognition, etc.). In PUIs, the human face is a central element, since it conveys not only identity but also other important information, particularly with respect to the user's mood or emotional state. This paper describes both a face detector and a smile detector for PUIs. Both are suitable for real-time interaction. The face detector provides eye, mouth and nose locations in frontal or nearly-frontal poses, whereas the smile detector is able to give a smile intensity measure. Experiments confirm that they are competitive with respect to extant detectors. These two detectors are used in an unobtrusive application that allows to interact with an Instant Messaging (IM) client.

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Acceleration and energy consumption optimization in cascading classifiers for face detection on low‐cost ARM big. LITTLE asymmetric architectures

Corpas

Costero

Botella

et al. 2018

Circuit Theory & Apps

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This paper proposes a mechanism to accelerate and optimize the energy consumption of a face detection software based on Haar-like cascading classifiers, taking advantage of the features of low-cost asymmetric multicore processors (AMPs) with limited power budget. A modelling and task scheduling/allocation is proposed in order to efficiently make use of the existing features on big. LITTLE ARM processors, including (1) source-code adaptation for parallel computing, which enables code acceleration by applying the OmpSs programming model, a task-based programming model that handles data-dependencies between tasks in a transparent fashion; (2) different OmpSs task allocation policies which take into account the processor asymmetry and can dynamically set processing resources in a more efficient way based on their particular features.The proposed mechanism can be efficiently applied to take advantage of the processing elements existing on low-cost and low-energy multi-core embedded devices executing object detection algorithms based on cascading classifiers.Although these classifiers yield the best results for detection algorithms in the field of computer vision, their high computational requirements prevent them from being used on these devices under real-time requirements. Finally, we compare the energy efficiency of a heterogeneous architecture based on AMPs with a suitable task scheduling with that of a homogeneous symmetric architecture.

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ENCARA2: Real-time detection of multiple faces at different resolutions in video streams

Cited by 167 publications

References 27 publications

Computer vision based eyewear selector

Computer vision based eyewear selector

Smile Detection for User Interfaces

Acceleration and energy consumption optimization in cascading classifiers for face detection on low‐cost ARM big. LITTLE asymmetric architectures

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