Kinship verification and recognition based on handcrafted and deep learning feature-based techniques.

BACKGROUND AND OBJECTIVES: Kinship verification and recognition (KVR) is the machine's ability to identify the genetic and blood relationship and its degree between humans' facial images. The face is used because it is one of the most significant ways to recognize each other. Automatic KVR is an interesting area for investigation. It greatly affects real-world applications, such as searching for lost family members, forensics, and historical and genealogical studies. This paper presents a comprehensive survey that describes KVR applications and kinship types. It presents a literature review of current studies starting from handcrafted passing through shallow metric learning and ending with deep learning feature-based techniques. Furthermore, kinship mostly used datasets are discussed that in turn open the way for future directions for the research in this field. Also, the KVR limitations are discussed, such as insufficient illumination, noise, occlusion, and age variations problems. Finally, future research directions are presented, such as age and gender variation problems. METHODS: We applied a literature survey methodology to retrieve data from academic databases. An inclusion and exclusion criteria were set. Three stages were followed to select articles. Finally, the main KVR stages, along with the main methods in each stage, were presented. We believe that surveys can help researchers easily to detect areas that require more development and investigation. RESULTS: It was found that handcrafted, metric learning, and deep learning were widely utilized in kinship verification and recognition problem using facial images. CONCLUSIONS: Despite the scientific efforts that aim to address this hot research topic, many future research areas require investigation, such as age and gender variation. In the end, the presented survey makes it easier for researchers to identify the new areas that require more investigation and research.

Can house sparrows recognize familiar or kin-related individuals by scent?

In the last decades, higher attention has been paid to olfactory perception in birds. As a consequence, a handful of avian species have been discovered to use olfaction in different contexts. Nevertheless, we still have a very limited knowledge about the use of odor cues in avian social life, particularly, in the case of songbirds. Here, we investigate if female house sparrows Passer domesticus show any preference for the odor of kin and nonkin conspecifics and we also test a possible role of familiarity based on male scent in female choice. We performed the experiment with captive birds twice, during the nonbreeding and breeding seasons. Our results show that female house sparrows strongly avoided the odor of unrelated familiar (UF) males, both in the breeding and nonbreeding seasons. Our results suggest recognition for olfactory stimuli related to familiarity and kinship. We suggest that avoidance for UF males is associated with previous experience in this species. Also, we provided further evidence to the use of olfaction in passerine species by using a new experimental setup.