Side-View Face Recognition

Side-view face recognition is a challenging problem with many applications. Especially in real-life scenarios where the environment is uncontrolled, coping with pose variations up to side-view positions is an important task for face recognition. In this paper we discuss the use of side view face recognition techniques to be used in house safety applications. Our aim is to recognize people as they pass through a door, and estimate their location in the house. Here, we compare available databases appropriate for this task, and review current methods for profile face recognition

Video-based Side-view Face Recognition for Home Safety

In this paper, we introduce a registration method for side-view face recognition that is suitable for home safety applications. We use cameras attached at door posts, and recognize people as they pass through doors to estimate their location in the house. First, we present a new database that is collected using this setup, where we use side cameras and ambient light. We recorded videos of 14 people that pass through doors in 18 different paths. Next, we propose our recognition method where we automatically find the profile to register the face images. By applying hierarchical clustering we detect the frames that include falsely detected profiles and pose variations, and automatically remove them from the video sequence to improve our results. After registering, we find the nose tip, apply recognition based on profiles, and analyze our results

Automatic face recognition for home safety using video-based side-view face images

Face recognition from side-view positions is an essential task for recognition systems with real-world scenarios. Most of the existing face recognition methods rely on alignment of face images into some canonical form. However, alignment in side-view faces can be challenging due to lack of symmetry and a small number of reliable reference points. To the best of the author's knowledge, only a few of the existing methods deal with video-based face recognition from side-view images, and not many databases include sufficient video footage to study this task. Here, the authors propose an automatic side-view face recognition system designed for home safety applications. They first contribute a newly collected video face database, named UT-DOOR, where 98 subjects were recorded with four cameras attached at doorposts as they pass through doors. Secondly, they propose a face recognition system, where they automatically detect and recognise faces using side-view images in videos. One of the attractive properties of this system is that they use cameras with limited view angle to preserve the privacy of the people. They review several databases and test their system both on the CMU Multi-PIE database and the UT-DOOR database for comparison. Experimental results show that their system can successfully recognise side-view faces from videos

Multimodální dialogový systém s podporou znakového jazyka

Tento článek popisuje návrh multimodálního dialogového systému s podporou znakové řeči. Jeho funkčnost byla testována na prototypu informačního kiosku pro neslyšící osoby, který poskytuje informace o vlakových spojeních. Systém využívá tyto vstupní modality: počítačové vidění, rozpoznávání znakového jazyka, automatické rozpoznávání řeči a dotykovou obrazovku. Výstupní modalitu představují 3D animace avatara na jedné obrazovce a grafické uživatelské rozhraní na druhé dotykové obrazovce. Informační kiosek může být použit pro sluchově postižené a neslyšící uživatelé v několika jazycích. Článek je zaměřen na popis vstupních a výstupních modalit vyjádřených znakovým jazykem.This paper presents the design of a multimodal sign-language-enabled dialogue system. Its functionality was tested on a prototype of an information kiosk for the deaf people providing information about train connections. We use an automatic computer-vision-based sign language recognition, automatic speech recognition and touchscreen as input modalities. The outputs are shown on a screen displaying 3D signing avatar and on a touchscreen displaying graphical user interface. The information kiosk can be used both by hearing users and deaf users in several languages. We focus on description of sign language input and output modality