Growth and fatty acid composition of Octopus vulgaris fed different diets based on bogue (Boops boops) in comparison to wild individuals

[EN] Octopus vulgaris is a suitable candidate to diversify marine aquaculture (Iglesias et al., 2000; Vaz Pires et al. 2004). Actually, wild sub-adults are on-growing in floating cages showing promising results (Chapela et al., 2006; Rodríguez et al., 2006). Even though octopus industrial development is still limited, mainly associated to the dependence of wild catch individuals for ongrowing (Iglesias et al., 2007) and a lack of an appropriate formulated diet (García García and Cerezo, 2006). In addition, essential macronutrient requirements for this species are still not well known. Used of discarded bogue as single food for Octopus on-growth results in similar growth than co-fed diets with the crab (Portunus pelagic). FA content of Muscle and DG showed important ARA content, suggesting the important functions of this FA in this specie.

Improving gender classification accuracy in the wild

[EN]In this paper, we focus on gender recognition in challenging large scale scenarios. Firstly, we review the literature results achieved for the problem in large datasets, and select the currently hardest dataset: The Images of Groups. Secondly, we study the extraction of features from the face and its local context to improve the recognition accuracy. Diff erent descriptors, resolutions and classfii ers are studied, overcoming previous literature results, reaching an accuracy of 89.8%.

Kinship verification in the wild: the first kinship verification competition

In this paper, we present the Kinship Verification in the Wild Competition: the first kinship verification competition which is held in conjunction with the International Joint Conference on Biometrics 2014, Clearwater, Florida, USA. The key goal of this competition is to compare the performance of different methods on a new-collected dataset with the same evaluation protocol and develop the first standardized benchmark for kinship verification in the wild.

The FG 2015 kinship verification in the wild evaluation

[ES]The aim of the Kinship Verification in the Wild Evaluation (held in conjunction with the 2015 IEEE International Conference on Automatic Face and Gesture Recognition, Ljubljana, Slovenia) was to evaluate different kinship verification algorithms. For this task, two datasets were made available and three possible experimental protocols (unsupervised, image-restricted, and image-unrestricted) were designed. Five institutions submitted their results to the evaluation: (i) Politecnico di Torino, Italy; (ii) LIRIS-University of Lyon, France; (iii) Universidad de Las Palmas de Gran Canaria, Spain; (iv) Nanjing University of Aeronautics and Astronautics, China; and (v) Bar Ilan University, Israel. Most of the participants tackled the image-restricted challenge and experimental results demonstrated better kinship verification performance than the baseline methods provided by the organizers.

On using periocular biometric for gender classification in the wild

[EN]Gender information may serve to automatically modulate interaction to the user needs, among other applications. Within the Computer Vision community, gender classification (GC) has mainly been accomplished with the facial pattern. Periocular biometrics has recently attracted researchers attention with successful results in the context of identity recognition. But, there is a lack of experimental evaluation of the periocular pattern for GC in the wild. The aim of this paper is to study the performance of this specific facial area in the currently most challenging large dataset for the problem.

Sea turtles recovered at the Wild Fauna Recovery Center in Gran Canaria (Canary Islands, Spain)

[EN] Since the beginning of the 1990's, the Wild Fauna Recovery Center in Gran Canaria Canary Islands, Spain) has received a large number of injured animals for recovery. Apart from birds and mammals, a considerable number of sea turtles representing different species are gathered each year. During the last five years (1999-2003), more than 100 turtles were sheltered annually; more than 80% successfully recovered and were released.

Multi-scale score level fusion of local descriptors for gender classification in the wild

The 2015 FRVT gender classification (GC) report evidences the problems that current approaches tackle in situations with large variations in pose, illumination, background and facial expression. The report suggests that both commercial and research solutions are hardly able to reach an accuracy over 90% for The Images of Groups dataset, a proven scenario exhibiting unrestricted or in the wild conditions. In this paper, we focus on this challenging dataset, stepping forward in GC performance by observing: 1) recent literature results combining multiple local descriptors, and 2) the psychophysics evidences of the greater importance of the ocular and mouth areas to solve this task...