221 research outputs found
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
Robust Re-Identification by Multiple Views Knowledge Distillation
To achieve robustness in Re-Identification, standard methods leverage tracking information in a Video-To-Video fashion. However, these solutions face a large drop in performance for single image queries (e.g., Image-To-Video setting). Recent works address this severe degradation by transferring temporal information from a Video-based network to an Image-based one. In this work, we devise a training strategy that allows the transfer of a superior knowledge, arising from a set of views depicting the target object. Our proposal - Views Knowledge Distillation (VKD) - pins this visual variety as a supervision signal within a teacher-student framework, where the teacher educates a student who observes fewer views. As a result, the student outperforms not only its teacher but also the current state-of-the-art in Image-To-Video by a wide margin (6.3% mAP on MARS, 8.6% on Duke-Video-ReId and 5% on VeRi-776). A thorough analysis - on Person, Vehicle and Animal Re-ID - investigates the properties of VKD from a qualitatively and quantitatively perspective
Combining feature aggregation and geometric similarity for re-identification of patterned animals
Image-based re-identification of animal individuals allows gathering of
information such as migration patterns of the animals over time. This, together
with large image volumes collected using camera traps and crowdsourcing, opens
novel possibilities to study animal populations. For many species, the
re-identification can be done by analyzing the permanent fur, feather, or skin
patterns that are unique to each individual. In this paper, we address the
re-identification by combining two types of pattern similarity metrics: 1)
pattern appearance similarity obtained by pattern feature aggregation and 2)
geometric pattern similarity obtained by analyzing the geometric consistency of
pattern similarities. The proposed combination allows to efficiently utilize
both the local and global pattern features, providing a general
re-identification approach that can be applied to a wide variety of different
pattern types. In the experimental part of the work, we demonstrate that the
method achieves promising re-identification accuracies for Saimaa ringed seals
and whale sharks.Comment: Camera traps, AI, and Ecology, 3rd International Worksho
Extracting Accurate Long-Term Behavior Changes from a Large Pig Dataset
Visual observation of uncontrolled real-world behavior leads to noisy observations, complicated by occlusions, ambiguity, variable motion rates, detection and tracking errors, slow transitions between behaviors, etc. We show in this paper that reliable estimates of long-term trends can be extracted given enough data, even though estimates from individual frames may be noisy. We validate this concept using a new public dataset of approximately 20+ million daytime pig observations over 6 weeks of their main growth stage, and we provide annotations for various tasks including 5 individual behaviors. Our pipeline chains detection, tracking and behavior classification combining deep and shallow computer vision techniques. While individual detections may be noisy, we show that long-term behavior changes can still be extracted reliably, and we validate these results qualitatively on the full dataset. Eventually, starting from raw RGB video data we are able to both tell what pigs main daily activities are, and how these change through time
Towards Automatic Honey Bee Flower-Patch Assays with Paint Marking Re-Identification
In this paper, we show that paint markings are a feasible approach to
automatize the analysis of behavioral assays involving honey bees in the field
where marking has to be as lightweight as possible. We contribute a novel
dataset for bees re-identification with paint-markings with 4392 images and 27
identities. Contrastive learning with a ResNet backbone and triplet loss led to
identity representation features with almost perfect recognition in closed
setting where identities are known in advance. Diverse experiments evaluate the
capability to generalize to separate IDs, and show the impact of using
different body parts for identification, such as using the unmarked abdomen
only. In addition, we show the potential to fully automate the visit detection
and provide preliminary results of compute time for future real-time deployment
in the field on an edge device.Comment: Paper 17, workshop "CV4Animals: Computer Vision for Animal Behavior
Tracking and Modeling", in conjunction with Computer Vision and Pattern
Recognition (CVPR 2023), June 18, 2023, Vancouver, Canad
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Chemocommunication and social behaviour in three Panthera species in captivity, with particular reference to the lion, P.leo
This project is a contribution towards the understanding of the mechanisms involved in
the chemocommunication systems of large mammals. Data are included on the social
behaviour and use of scent marking for the African lion, P. leo as well as two other
Panthera species namely the Siberian tiger, P. tigris altaica, and the leopard, P. pare/us.
The study was conducted in three Zoos or Safariparks in Denmark: K0benhavn Zoo,
Givskud Safaripark and Knuthenborg Safaripark.
Data were collected in three ways. The first part of the project comprised behavioural
observations of the undisturbed social and marking patterns of the study groups. Particular
attention was paid towards Spraymarking, Scrape/urination and normal Urination but
Clawing, Chinrubbing and Defaecation were also recorded. Methods were developed
which made it possible to collect samples of scent marks from the study animals. The
scent samples collected were used in the second part of the field work, which involved an
experimental investigation in which the animals were presented with scent marks from
foreign individuals of varying sex, age or reproductive status. These experiments were
conducted both in the "natural" setting of the outdoor enclosures as well as in the artificial
surroundings of the night cages of the animals. In the third and final part of the study the
scent mark samples collected were subjected to chemical analysis using the "Headspace"
procedure on a combined Gas Chromatograph and Mass Spectrometre.
The activity and social interactions of the animals, although under influence of the
captive environment, were generally close to what one would expect to see for wild
animals. Each animal showed a distinct activity pattern and social repertoire, but more
general differences between the sex/age groups were also found. Males tended to stand
more than females or cubs and show higher levels of Investigation, whereas females
generally moved more than males. Cubs played more than the two adult groups. These
trends were seen in all three species.
Each animal had a distinct marking repertoire, but generally the male patterns were
dominated by Sprayrmarking followed by Scrape/urination, whereas the female patterns
were much more variable. Male lions had higher rates of Spraymarking and significantly
higher rates of Scrape/urination than females. No significant difference was found
between Sprayrnarking rates of male and female tigers, but both had significantly higher
rates than castrated tiger males. The leopard male had higher rates of the two marking
types than the female.
Male lions showed a bias towards Spraymarking over Scrape/urination in territorial
contexts, but no such bias in social contexts. The females showed no bias in markings in
either context.
Investigation of experimental marks were dominated by Scenting and Flehmen and
very little Licking and Overmarking was seen.
In the chemical analysis 58 compounds were identified in lion urine samples. Lion
male samples overlapped significantly more in compound composition with other male
samples than they did with female samples. The majority of the lions overlapped more
within their own samples than they did with samples from other lions, and for seven out of
16 lions this difference was significant. Male lions had a significantly higher absolute
concentration of 2-butanone than females, and females had a significantly higher relative
concentration of acetone than did males.
57 compounds were identified in tiger urine samples. All tigers overlapped more
within their own samples than between theirs and other samples from same sex
individuals, but only one significantly so. Castrated tiger males had higher concentration
of 5-hydroxy-4-methyl-6-hepten-3-one than the intact male.
In leopard urine samples 18 compounds were identified.
Possible candidates for species and sex identifying compounds were put forward for
lions and tigers. On average two lion samples overlapped significantly more in compound
composition thall did a lion sample and a tiger sample. This was also the case for the
overlap between two tiger samples compared to a tiger and a lion sample. Leopard
samples overlapped equally with lion and tiger samples.
The results are discussed in relation to what is known about the same species living in
the wild. Furthermore the use of chemical signals are discussed in relation to their
chemical and physical properties, and their function in a territorial context is commented
upon
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