公开(公告)号：US20240362797A1

公开(公告)日：2024-10-31

申请号：US18639001

申请日：2024-04-18

Applicant: Wildlife Imaging Systems LLC

Inventor： Brogan Page Morton ,  Jonathan Ritter

IPC: G06T7/20 ,  G06T7/12 ,  G06T7/194 ,  G06T7/62 ,  G06T7/70 ,  G06V10/40

CPC classification number: G06T7/20 ,  G06T7/12 ,  G06T7/194 ,  G06T7/62 ,  G06T7/70 ,  G06V10/40 ,  G06T2207/10016 ,  G06V2201/07

Abstract: A system and associated methods are disclosed for automatically detecting, tracking and classifying an at least one object, moving within an environment proximal to a structure, using a camera. In at least one embodiment, a processor receives a plurality of video frames as captured by the camera. For each of the video frames, the processor detects the presence of the at least one object within said video frame, creates a track for each of the at least one detected object, identifies each track as either an acceptable track or noise, classifies each of the acceptable tracks, and generates an at least one summary image that visually represents the at least one detected object within the environment proximal to the structure, allowing for validation and performance evaluation of the object detection, tracking, and classification process.

公开(公告)号：US20240362441A1

公开(公告)日：2024-10-31

申请号：US18140550

申请日：2023-04-27

Applicant: ZEBRA TECHNOLOGIES CORPORATION

Inventor： Edward Barkan ,  Darran Michael Handshaw ,  Mark Drzymala ,  David P. Goren ,  Binyamin Stein

IPC: G06K7/14 ,  G06T7/40 ,  G06T7/50 ,  G06T7/62 ,  G06V10/74 ,  G06V40/10

CPC classification number: G06K7/1443 ,  G06T7/40 ,  G06T7/50 ,  G06T7/62 ,  G06V10/761 ,  G06V40/107 ,  G06T2207/30242 ,  G06V2201/07

Abstract: The present disclosure provides new and innovative devices, methods, and apparatuses for discerning the presence and characteristics of objects that are passing in front of an indicia decoding device. In an example, a device comprises a 2D imaging assembly, a depth imaging assembly, and a processing device configured to analyze data from the depth imaging assembly to determine a number of items that are in a field of view of the depth imaging assembly during a period of time, analyze data from the 2D imaging assembly to determine a number of indicia that are present in a field of view of the 2D imaging assembly during at least a portion of the period of time, compare the number of indicia with the number of items, output a determination as to whether the number of indicia matches the number of items, and responsive to determining that the number of indicia does not match the number of items, transmit a message to an alert module.

公开(公告)号：US20240362438A1

公开(公告)日：2024-10-31

申请号：US18140587

申请日：2023-04-27

Applicant: ZEBRA TECHNOLOGIES CORPORATION

Inventor： Darran Michael Handshaw ,  Edward Barkan ,  Mark Drzymala ,  David P. Goren ,  Binyamin Stein

IPC: G06K7/10 ,  G06T7/50 ,  G06T7/70 ,  G06V10/74 ,  G06V40/10

CPC classification number: G06K7/10722 ,  G06T7/50 ,  G06T7/70 ,  G06V10/761 ,  G06V40/107 ,  G06T2207/10024 ,  G06T2207/30196 ,  G06V2201/07

Abstract: The present disclosure provides new and innovative systems, methods, and apparatuses for detecting non-decode events in indicia scanning settings. In an example, a system comprises a depth imaging assembly, a 2D imaging assembly, and a processing device, wherein the processing device is configured to attempt to decode an indicium affixed to a first item that is passing through at least one of a field of view of the 2D imaging assembly or a field of view of the depth imaging assembly, determine a first characteristic associated with the first item based on depth data from the depth imaging array, and responsive to a failed attempt to decode the indicium, detect a second item that is passing through the field of view of the 2D imaging assembly and the field of view of the depth imaging assembly, determine a second characteristic associated with the second item based on depth data from the depth imaging assembly, determine if the first item is a same item as the second item based on comparing the first characteristic and the second characteristic, and responsive to determining that the first item and the second item are not the same item, transmit a message to an alert module that is indicative of a non-decode event.

公开(公告)号：US12131548B2

公开(公告)日：2024-10-29

申请号：US17769343

申请日：2020-04-15

Applicant: ASELSAN ELEKTRONIK SANAYI VE TICARET ANONIM SIRKETI

Inventor： Engin Uzun ,  Tolga Aksoy ,  Erdem Akagunduz

IPC: G06V10/82 ,  G06T5/20 ,  G06V10/32 ,  G06V10/44 ,  G06V10/94 ,  G06V20/52 ,  G06V20/56

CPC classification number: G06V20/56 ,  G06T5/20 ,  G06V10/32 ,  G06V10/454 ,  G06V10/82 ,  G06V10/94 ,  G06V20/52 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06V2201/07

Abstract: Disclosed is a method for training shallow convolutional neural networks for infrared target detection using a two-phase learning strategy that can converge to satisfactory detection performance, even with scale-invariance capability. In the first step, the aim is to ensure that only filters in the convolutional layer produce semantic features that serve the problem of target detection. L2-norm (Euclidian norm) is used as loss function for the stable training of semantic filters obtained from the convolutional layers. In the next step, only the decision layers are trained by transferring the weight values in the convolutional layers completely and freezing the learning rate. In this step, unlike the first, the L1-norm (mean-absolute-deviation) loss function is used.

公开(公告)号：US12131547B2

公开(公告)日：2024-10-29

申请号：US18383148

申请日：2023-10-24

Applicant: NEC Corporation

Inventor： Junko Nakagawa ,  Ryoma Oami ,  Kenichiro Ida ,  Mika Saito ,  Shohzoh Nagahama ,  Akinari Furukawa ,  Yasumasa Ohtsuka ,  Junichi Fukuda ,  Fumi Ikeda ,  Manabu Moriyama ,  Fumie Einaga ,  Tatsunori Yamagami ,  Keisuke Hirayama ,  Yoshitsugu Kumano ,  Hiroki Adachi

IPC: G06K9/00 ,  G06F16/22 ,  G06Q50/26 ,  G06V20/40 ,  G06V20/52 ,  G06V40/10 ,  H04N7/18

CPC classification number: G06V20/52 ,  G06F16/22 ,  G06Q50/265 ,  G06V20/40 ,  G06V20/41 ,  G06V20/46 ,  G06V40/10 ,  G06V2201/07 ,  G06V2201/08 ,  H04N7/18

Abstract: An information processing apparatus (10) includes a time and space information acquisition unit (110) that acquires high-risk time and space information indicating a spatial region with an increased possibility of an accident occurring or of a crime being committed and a corresponding time slot, a possible surveillance target acquisition unit (120) that identifies a video to be analyzed from among a plurality of videos generated by capturing an image of each of a plurality of places, on the basis of the high-risk time and space information, and analyzes the identified video to acquire information of a possible surveillance target, and a target time and space identification unit (130) that identifies at least one of a spatial region where surveillance is to be conducted which is at least a portion of the spatial region or a time slot when surveillance is to be conducted, from among the spatial region and the time slot indicated by the high-risk time and space information, on the basis of the information of the possible surveillance target.

公开(公告)号：US12131484B1

公开(公告)日：2024-10-29

申请号：US18732676

申请日：2024-06-04

Applicant: Zhejiang University

Inventor： Yunfeng Yan ,  Haoyuan Jin ,  Donglian Qi ,  Qi Li ,  Rui Han ,  Bingxiao Mei ,  Zezhou Wang ,  Gang Chen

IPC: G06T7/20 ,  G06T5/20 ,  G06T7/11 ,  G06V10/44 ,  G06V10/80

CPC classification number: G06T7/20 ,  G06T5/20 ,  G06T7/11 ,  G06V10/44 ,  G06V10/806 ,  G06V2201/07

Abstract: A multi-object tracking method based on authenticity hierarchizing and occlusion recovery relates to the technical field of multi-object tracking for security management and control of complex scenes. The method includes the following steps: image acquisition, object detection, authenticity hierarchizing, hierarchical association and outputting tracks. The multi-object tracking method is helpful to solve the long-term puzzling occlusion problem in the field of multi-object tracking, the constructed new algorithm framework can achieve an advanced tracking performance, improve the adaptability of the method to complex environments, and adapt to more difficult video surveillance security control tasks.

公开(公告)号：US12131466B2

公开(公告)日：2024-10-29

申请号：US17806402

申请日：2022-06-10

Applicant: Tata Consultancy Services Limited

Inventor： Manu Sheoran ,  Meghal Dani ,  Monika Sharma ,  Lovekesh Vig

IPC: G06T7/00 ,  G06V10/25 ,  G06V10/26 ,  G06V10/44 ,  G06V10/778

CPC classification number: G06T7/0012 ,  G06V10/25 ,  G06V10/26 ,  G06V10/454 ,  G06V10/778 ,  G06T2207/10081 ,  G06T2207/30096 ,  G06V2201/032 ,  G06V2201/07

Abstract: State of the art deep network based Universal Lesion Detection (ULD) techniques inherently depend on large number of datasets for training the systems. Moreover, these system are specifically trained for lesion detection in organs of a Region of interest (RoI) of a body. Thus, requires retraining when the RoI varies. Embodiments herein disclose a method and system for domain knowledge augmented multi-head attention based robust universal lesion detection. The method utilizes minimal number of Computer Tomography (CT) scan slices to extract maximum information using organ agnostic HU windows and a convolution augmented attention module for a computationally efficient ULD with enhanced prediction performance.

公开(公告)号：US12129191B1

公开(公告)日：2024-10-29

申请号：US18779609

申请日：2024-07-22

Applicant: Nishant Narayanan

Inventor： Nishant Narayanan

IPC: G06V30/148 ,  C02F1/50 ,  G06F3/02 ,  G06F7/24 ,  G06F18/20 ,  G06F18/213 ,  G06V10/82 ,  G06V20/56 ,  G06V20/62 ,  G06V20/69 ,  C02F103/00

CPC classification number: C02F1/50 ,  G06V10/82 ,  G06V20/56 ,  G06V20/69 ,  C02F2103/007 ,  C02F2201/008 ,  C02F2209/006 ,  G06V2201/07

Abstract: A system for monitoring and improving water quality by mitigating harmful algal blooms. The system comprises an automatic detection unit that is configured to affix to an unmanned vehicle (UV). The automatic detection unit is adapted to detect harmful algal blooms in a water body when the UV flies over it. The automatic detection unit communicates to a server via a network. This automated process ensures swift identification without human intervention, enhancing efficiency. The system performs real-time data transmission that allows for analysis and response, facilitating timely decisions and interventions to mitigate algal blooms. The system is integrated with an artificial intelligence module, trained on reference data using convolution neural networks (CNNs). By automating detection, analysis, and response processes, the system optimizes operational efficiency, reducing manual effort and response times in managing algal bloom incidents.

公开(公告)号：US20240351385A1

公开(公告)日：2024-10-24

申请号：US18509740

申请日：2023-11-15

Applicant: Hyundai Motor Company ,  Kia Corporation

Inventor： Joo Han NAM

IPC: B60D1/36 ,  B60D1/46 ,  G05D1/10 ,  G06V20/17 ,  H04W4/40 ,  H04W4/80

CPC classification number: B60D1/36 ,  B60D1/465 ,  G06V20/17 ,  H04W4/40 ,  H04W4/80 ,  G06V2201/07 ,  G06V2201/08

Abstract: The present disclosure relates to a device, an air mobility, a server, and a method for controlling a vehicle. The device includes a communication device, a memory storing vehicle information and air mobility device information, and a processor. The processor is configured to select, based on the vehicle information, a target vehicle to be coupled to a trailer, select, based on the air mobility device information, a target air mobility device, and transmit, via the communication device, at least one signal. The at least signal includes an indication for requesting the target vehicle to move to a location of the trailer, and an indication for requesting the target air mobility device to capture at least one image containing the target vehicle and the trailer.

公开(公告)号：US12125284B2

公开(公告)日：2024-10-22

申请号：US17784472

申请日：2020-10-13

Applicant: Hitachi, Ltd.

Inventor： Masato Tamura ,  Tomoaki Yoshinaga ,  Atsushi Hiroike ,  Hiromu Nakamae ,  Yuta Yanashima

IPC: G06V20/52 ,  G06V10/82 ,  G06V20/64

CPC classification number: G06V20/52 ,  G06V10/82 ,  G06V20/647 ,  G06V2201/07

Abstract: An object of the invention is to configure an object search device capable of expressing information on shapes and irregularities as features only by images, in a search for an object that is characteristic in shape or irregularity, and performing an accurate search.
The object search device includes: an image feature extraction unit that is configured with a first neural network, and is configured to input an image to extract an image feature; a three-dimensional data feature extraction unit that is configured with a second neural network, and is configured to input three-dimensional data to extract a three-dimensional data feature; a learning unit that is configured to extract an image feature and a three-dimensional data feature from an image and three-dimensional data of an object obtained from a same individual, respectively, and update an image feature extraction parameter so as to reduce a difference between the image feature and the three-dimensional data feature; and a search unit that is configured to extract image features of a query image and a gallery image of the object by the image feature extraction unit using the updated image feature extraction parameter, and calculate a similarity between the image features of both images to search for the object.