ATRW: A Benchmark for Amur Tiger Re-identification in the Wild

Monitoring the population and movements of endangered species is an important task to wildlife conversation. Traditional tagging methods do not scale to large populations, while applying computer vision methods to camera sensor data requires re-identification (re-ID) algorithms to obtain accurate counts and moving trajectory of wildlife. However, existing re-ID methods are largely targeted at persons and cars, which have limited pose variations and constrained capture environments. This paper tries to fill the gap by introducing a novel large-scale dataset, the Amur Tiger Re-identification in the Wild (ATRW) dataset. ATRW contains over 8,000 video clips from 92 Amur tigers, with bounding box, pose keypoint, and tiger identity annotations. In contrast to typical re-ID datasets, the tigers are captured in a diverse set of unconstrained poses and lighting conditions. We demonstrate with a set of baseline algorithms that ATRW is a challenging dataset for re-ID. Lastly, we propose a novel method for tiger re-identification, which introduces precise pose parts modeling in deep neural networks to handle large pose variation of tigers, and reaches notable performance improvement over existing re-ID methods. The dataset is public available at https://cvwc2019.github.io/ .Comment: ACM Multimedia (MM) 202

Discrimination of Individual Tigers (\u3cem\u3ePanthera tigris\u3c/em\u3e) from Long Distance Roars

This paper investigates the extent of tiger (Panthera tigris) vocal individuality through both qualitative and quantitative approaches using long distance roars from six individual tigers at Omaha\u27s Henry Doorly Zoo in Omaha, NE. The framework for comparison across individuals includes statistical and discriminant function analysis across whole vocalization measures and statistical pattern classification using a hidden Markov model (HMM) with frame-based spectral features comprised of Greenwood frequency cepstral coefficients. Individual discrimination accuracy is evaluated as a function of spectral model complexity, represented by the number of mixtures in the underlying Gaussian mixture model (GMM), and temporal model complexity, represented by the number of sequential states in the HMM. Results indicate that the temporal pattern of the vocalization is the most significant factor in accurate discrimination. Overall baseline discrimination accuracy for this data set is about 70% using high level features without complex spectral or temporal models. Accuracy increases to about 80% when more complex spectral models (multiple mixture GMMs) are incorporated, and increases to a final accuracy of 90% when more detailed temporal models (10-state HMMs) are used. Classification accuracy is stable across a relatively wide range of configurations in terms of spectral and temporal model resolution

A Postulate for Tiger Recovery: The Case of the Caspian Tiger

Recent genetic analysis has shown that the extinct Caspian Tiger (P. t. virgata) and the living Amur Tigers (P. t. altaica) of the Russian Far East are actually taxonomically synonymous and that Caspian and Amur groups historically formed a single population, only becoming separated within the last 200 years by human agency. A major conservation implication of this finding is that tigers of Amur stock might be reintroduced, not only back into the Koreas and China as is now proposed, but also through vast areas of Central Asia where the Caspian tiger once lived. However, under the current tiger conservation framework the 12 “Caspian Tiger States” are not fully involved in conservation planning. Equal recognition as “Tiger Range States” should be given to the countries where the Caspian tiger once lived and their involvement in tiger conservation planning encouraged. Today, preliminary ecological surveys show that some sparsely populated areas of Central Asia preserve natural habitat suitable for tigers. In depth assessments should be completed in these and other areas of the Caspian range to evaluate the possibility of tiger reintroductions. Because tigers are a charismatic umbrella species, both ecologically and politically, reintroduction to these landscapes would provide an effective conservation framework for the protection of many species in addition to tigers. And for today’s Amur Tigers this added range will provide a buffer against further loss of genetic diversity, one which will maintain that diversity in the face of selective pressures that can only be experienced in the wild

Diet of Bengal Tigers (Panthera tigris tigris) in Chitwan National Park, Nepal

We studied the diet of the Bengal tigers (Panthera tigris tigris) in Chitwan National Park, Nepal, by identifying 109 prey items from 85 tiger scats. Tigers in this region fed upon eight different mammal species. Chital (Axis axis) was the major prey with a frequency of 45% of the Tigers’ diet. The occurrence of other prey species included sambar (Cervus unicolor, 23%), wild pig (Sus scrofa, 15%), hog deer (Axis porcinus, 9%), barking deer (Muntiacus muntjak, 4%), and gaur (Bos gaurus, 2%). Tigers also hunted livestock, but this prey comprised a small component of the relative biomass (buffalo 5% and cow 2%). Our study suggests that the tiger depends mostly upon wild prey for its subsistence in the Chitwan National Park, but will also sporadically hunt livestock

Mitochondrial Phylogeography Illuminates the Origin of the Extinct Caspian Tiger and Its Relationship to the Amur Tiger

The Caspian tiger (Panthera tigris virgata) flourished in Central Asian riverine forest systems in a range disjunct from that of other tigers, but was driven to extinction in 1970 prior to a modern molecular evaluation. For over a century naturalists puzzled over the taxonomic validity, placement, and biogeographic origin of this enigmatic animal. Using ancient-DNA (aDNA) methodology, we generated composite mtDNA haplotypes from twenty wild Caspian tigers from throughout their historic range sampled from museum collections. We found that Caspian tigers carry a major mtDNA haplotype differing by only a single nucleotide from the monomorphic haplotype found across all contemporary Amur tigers (P. t. altaica). Phylogeographic analysis with extant tiger subspecies suggests that less than 10,000 years ago the Caspian/Amur tiger ancestor colonized Central Asia via the Gansu Corridor (Silk Road) from eastern China then subsequently traversed Siberia eastward to establish the Amur tiger in the Russian Far East. The conservation implications of these findings are far reaching, as the observed genetic depletion characteristic of modern Amur tigers likely reflects these founder migrations and therefore predates human influence. Also, due to their evolutionary propinquity, living Amur tigers offer an appropriate genetic source should reintroductions to the former range of the Caspian tiger be implemented

Oldest known pantherine skull and evolution of the tiger

The tiger is one of the most iconic extant animals, and its origin and evolution have been intensely debated. Fossils attributable to extant pantherine species-lineages are less than 2 MYA and the earliest tiger fossils are from the Calabrian, Lower Pleistocene. Molecular studies predict a much younger age for the divergence of modern tiger subspecies at <100 KYA, although their cranial morphology is readily distinguishable, indicating that early Pleistocene tigers would likely have differed markedly anatomically from extant tigers. Such inferences are hampered by the fact that well-known fossil tiger material is middle to late Pleistocene in age. Here we describe a new species of pantherine cat from Longdan, Gansu Province, China, Panthera zdanskyi sp. nov. With an estimated age of 2.55–2.16 MYA it represents the oldest complete skull of a pantherine cat hitherto found. Although smaller, it appears morphologically to be surprisingly similar to modern tigers considering its age. Morphological, morphometric, and cladistic analyses are congruent in confirming its very close affinity to the tiger, and it may be regarded as the most primitive species of the tiger lineage, demonstrating the first unequivocal presence of a modern pantherine species-lineage in the basal stage of the Pleistocene (Gelasian; traditionally considered to be Late Pliocene). This find supports a north-central Chinese origin of the tiger lineage, and demonstrates that various parts of the cranium, mandible, and dentition evolved at different rates. An increase in size and a reduction in the relative size of parts of the dentition appear to have been prominent features of tiger evolution, whereas the distinctive cranial morphology of modern tigers was established very early in their evolutionary history. The evolutionary trend of increasing size in the tiger lineage is likely coupled to the evolution of its primary prey species

Tiger Monitoring in Bhutan Using Non-invasive Genetic Tools

Large carnivores are one of the most threatened group of animals in the world. They suffer from prey depletion, persecution by humans, and habitat loss and fragmentation which are extensively driven by anthropogenic activities. One such species is the tiger Panthera tigris. Tigers are found in thirteen countries in Asia and are protected across the range; however, tiger numbers have declined as an after effect of habitat loss, prey depletion and poaching. Human-induced changes have reduced the tiger\u27s historical range to about 7% in which a little more than 3900 tigers are found. Most of these individuals currently exist in small and highly structured populations. Obtaining reliable estimates of population size and density and a solid understanding of the connectivity between populations are critical to understanding crucial aspects of effective tiger conservation. Bhutan, with a vast expanse of contiguous pristine forest cover, abundant prey, and active conservation policies, form a very critical part of tiger conservation in South Asia. However, due to limited funds, monitoring is erratic. Camera traps are a sought-after tool for monitoring tiger population and density in Bhutan, but costs have been a limiting factor. Therefore, we evaluated non-invasive genetic sampling (NGS) as an effective alternative to camera trapping for monitoring tigers in Bhutan. We carried out systematic camera trap and scat surveys in Royal Manas National Park in Southern Bhutan in 2018 and compared density, variability, and costs between the two methods. The densities were estimated under a spatially-explicit capture-recapture framework, and camera trap and NGS produced a density of 2.38 tigers/100 km2(95% CI 1.11-4.02) and 3.6 tigers/100km2(95% CI 1.06-12.23) respectively. Density and other parameters were estimated more precisely using camera traps, but the field and equipment cost was high as compared to single-session genetic sampling. When controlled for sampling effort, NGS performed better. There is also no information regarding population connectivity and gene flow in tigers within Bhutan. We genotyped 24 individuals using thirteen microsatellite loci and found that Bhutanese tigers overall have a high genetic variation (He=0.75). Individual-based and multivariate analyses indicated three genetic clusters within the sampled individuals; however, the overall genetic differentiation was low (FST=0.44). Our results suggest that Bhutanese tigers can be a source of genetic variation in the region and could play a crucial role in the long-term persistence of the species. We strongly recommend a transboundary and landscape-level conservation approach using common genetic data sets to understand tiger dispersal, threats, and other factors influencing dispersal events

Resource Partitioning and Density Drivers of Two Endangered Large Felids: Amur Tiger (Panthera Tigris Altaica) and Amur Leopard (Panthera Pardus Orientalis) In the Russian Far East

In Russia, long-term conservation interventions have bolstered the critically endangered Amur leopard (Panthera pardus orientalis) as well as their dominant competitor, the endangered Amur tiger (Panthera tigris altaica). Within the Land of the Leopard National Park, I investigated the potential for tigers to displace or suppress leopards. I used data from winter track surveys to fit resource selection functions and camera trap surveys to both fit spatially-explicit capture-recapture models and document leopard productivity. I found no evidence of habitat displacement or numerical limitation of leopards by tigers in this region. Leopards resource selection was defined by landscape features and density was explained by the putative availability of sika deer rather than competition from tigers. Lastly, the number of observed leopard litters of all ages increased positively with local tiger density. This research lays an important foundation for conservation actions that prioritize minimizing human impacts on both felids rather than limiting tigers to benefit leopards

Fast and Efficient Model for Real-Time Tiger Detection In The Wild

The highest accuracy object detectors to date are based either on a two-stage approach such as Fast R-CNN or one-stage detectors such as Retina-Net or SSD with deep and complex backbones. In this paper we present TigerNet - simple yet efficient FPN based network architecture for Amur Tiger Detection in the wild. The model has 600k parameters, requires 0.071 GFLOPs per image and can run on the edge devices (smart cameras) in near real time. In addition, we introduce a two-stage semi-supervised learning via pseudo-labelling learning approach to distill the knowledge from the larger networks. For ATRW-ICCV 2019 tiger detection sub-challenge, based on public leaderboard score, our approach shows superior performance in comparison to other methods